#Free Harvard Reference Generator

[religion-is-a-mental-illness]

By: Dan Zaksheske

Published: Apr 22, 2025

The New York Times published more than 10,000 words about former San Jose State volleyball player Blaire Fleming over the weekend. Fleming is a biological male who identifies as a woman, who competed on the women's team and who helped make the Spartans one of the top teams in their conference. 

Buried deep in the story was a single paragraph that should raise some eyebrows. The author mentions Joanna Harper, a biological male who identifies as a woman and purportedly studies transgender athletes. It's important to note that Harper played an advisory role in the 2015 Olympics transgender decision allowing males to compete in women's Olympic events with testosterone suppression.

But that's not the interesting part. 

"Harper is currently helping to lead an ambitious study of trans adolescents that measures their results on a 10-step fitness test before they start hormone therapy and then, after they have begun to medically transition, every six months for five years," the NYT story reads. 

It continues, "But, she told me when we talked in February, ‘the current climate makes the study somewhat uncertain.’ I assumed she was referring to the Trump administration’s cuts to National Institutes of Health research grants, but she said money was not a problem: The study is being funded by Nike. The problem was Trump’s separate order targeting medical care for transgender youth. ‘If we can’t perform gender-affirming care,’ she explained, ‘then we can’t bring people into the study.’" 

Wait, "the study is being funded by Nike?" Why is a sports apparel company allegedly funding research that focuses on children and young teenagers taking potentially life-altering medications simply to try and prove that males should be allowed in girls' and women's sports? Basic common sense tells us they shouldn't.

Unfortunately, Nike won't answer this question. OutKick has attempted to reach the company several times, and they have not responded. OutKick spoke with sources who had also tried to ask Nike about the study, to no avail. 

In addition, the company has an entire page on its website – titled "No Pride, No Sport" – dedicated to gender ideology causes. Here's what the mission statement reads: "Nike is on a mission to make sport available to everyone, everywhere. We’re continuing our commitment to helping shape a strong culture of LGBTQIA+ belonging and visibility in sport. We’re working to expand sport for the next generation through community grants, athlete partnerships, impactful storytelling, and products that celebrate the full spectrum of LGBTQIA+ expression. Because sport is better when all athletes are free to play as themselves." 

On this page, Nike lists many of the different ways that the company is pushing the ideas of the radical left-wing. This includes partnering with an organization called "The GenderCool Project," which is an "educational campaign sharing powerful, impactful stories about trans and non-binary youth in sport." 

There's also the organization "Not a Phase," which is a "trans-led grassroots movement working to uplift and improve the lives of trans and nonbinary adults through education, funding, and community project initiatives." 

The one area that's conspicuously absent is the study mentioned in the New York Times article, the one that Nike is reportedly helping to fund. The study, led by Kathryn Ackerman of Boston Children's Hospital and an Associate Professor of Medicine at Harvard Medical School, also includes Joanna Harper and several other researchers. 

Sarah Barker, author of the Substack The Female Category, did a deep-dive into the study itself and the other alleged financial contributors back in October. 

While Nike has not confirmed their financial contribution to the study, Ackerman has said on several occasions that the company is, indeed, providing them with money. 

During a seminar in 2023, Ackerman stated, "Recently, we got some money from Nike, who wanted to study this more… they wanted to look at transgender folks who are going through the transition younger. So, if we are talking about athletes who are pausing puberty and then doing gender-affirming care and cross-hormonal treatment, what happens to them over time." 

Ackerman made it sound like Nike approached her, not the other way around. Again, why? Why is Nike so invested in seeing what happens to pre-pubescent children when they are given potentially harmful and life-altering medications, hormones and surgeries? 

This is a company that constantly preaches about women's sports, and how dedicated it is to supporting women, yet they are allegedly helping to fund a study to see just how much medication male children need to "fairly" compete in women's sports? 

While Ackerman and Harper have both publicly noted Nike's financial interest in the study, during a conference in 2024, Harper discussed the methods of the study but did not disclose Nike providing funding. According to a source, this was very strange. 

"Nothing was stated about Nike… in the presentation; research presentations should always disclose project funders at the end of a slide show. It is not normal for a scientific presentation to exclude funding sources," the source told OutKick. 

So, what is going on here? Well, that's unclear because Nike doesn't seem interested in disclosing its role, if any, in the research. However, allegedly funding a researcher who is a "transgender activist" who then hired a "transgender" PhD to help with the study, makes it seem pretty clear what result they hope to achieve. 

It appears they want a study that says if doctors stop young males from going through puberty – with pharmaceutical intervention – and "transition" them as early as possible, there's no reason they shouldn't be allowed to compete in girls' and women's sports. And, if that study is produced, what is the endgame? To have as many little boys as possible put on puberty-blockers and hormones in a rush to head off puberty? 

How is it possible that more people don't realize how insane that sounds? If this is true, shame on those researchers and shame on Nike. The company would be participating in experiments on kids that our society should qualify as child abuse. Truly disgusting. 

--

By: Dan Zaksheske

Published: April 25, 2025

As OutKick previously reported, Dr. Kathryn Ackerman and researcher Joanna Harper have both publicly stated that Nike is helping to fund a study on youth transgender athletes as young as 12 years old. At first, Nike did not respond to requests about the study to confirm or deny their involvement. 

However, with public pressure mounting, a Nike executive with knowledge of the situation finally contacted OutKick. According to the executive, the study "was never initialized" and "is not moving forward." But what exactly does that mean? Unfortunately, Nike has not provided any clarity. 

OutKick asked the Nike executive if Dr. Ackerman and Harper were wrong to say that Nike funded the study, something both have said multiple times since 2023 and as recently as 2025. The executive said "no one was wrong" but that there might have been some "gaps in the information chain." Again, what does that mean? 

Unfortunately, OutKick also did not receive a response from Dr. Ackerman, who we attempted to reach through multiple means, including her positions at the Boston Children's Hospital, Harvard Medical School and The Female Athlete Conference. 

OutKick also contacted Sarah Sowers, the Director of Research Partnerships at the Nike Sport Research Lab. Sowers was referenced specifically by Ackerman during one of her presentations, but Sowers instructed us to contact Nike media relations. 

The New York Times, in their story about transgender volleyball player Blaire Fleming, also reported that Nike was funding the study. OutKick asked the Times if Nike contacted the outlet to demand a retraction. 

"We are confident in the accuracy of our reporting," a New York Times spokesperson told OutKick. 

So, what do we know? We know that during a seminar in 2023, Ackerman stated, "Recently, we got some money from Nike, who wanted to study this more… they wanted to look at transgender folks who are going through the transition younger. So, if we are talking about athletes who are pausing puberty and then doing gender-affirming care and cross-hormonal treatment, what happens to them over time." 

We know that Harper told the New York Times that Nike is funding the study and the New York Times stands by its reporting. We know that Nike now says that the study "was never initialized" and "is not moving forward." What we don't know is if Nike actually provided any funds in the first place, when the decision was made not to "move forward," who might have made that decision, or why they made it. 

Like we said, more questions than answers. Unfortunately, Nike has decided to leave these questions unanswered. 

==

Let me translate: yes, it was all completely true, but now they're hastily shutting it down and covering it up.

[the-sweet-hibiscus]

On Plagiarism in Fandom

AKA the For Want of a Nail Situation

Please Note: This is Not A Witch Hunt. Do not Harass, Attack, or otherwise attempt to cause harm to the people mentioned in this list. This post is just to highlight and bring awareness to the plagiarism and pattern of behavior within the community, and to see where we should go from here.

On Plagiarism Itself

At the end of 2023, it seemed that the topic of plagiarism on the internet garnered a renewed vigor following the four-hour HBomberguy video on YouTube Plagiarism. The video was extremely well researched, calling out several instances of plagiarism on the site, and spent nearly half it's run time discussing the egregiousness of one specific content creator, James Somerton. Which I found interesting.

During the time of that video's release, coincidentally, in the academic world several high-profile academics – such as the ex-President of Harvard and former MIT professors – began facing their own allegations of plagiarism and improperly sourcing Wikipedia for their massive papers. There, of course, are several other instances of plagiarism in the publishing/book world.

Lauren M. Davis falsely accused a fellow author of plagiarism and faced the backlash for it (amongst other serious issues, but it started with the plagiarism.) Mark Dawson is currently facing accusations of plagiarism in several of his 20+ works. If you go back you can find a multitude of instances where plagiarism has been called out, and consequences are faced the perpetrators.

I only mention these instances as a baseline to frame that both creatively and academically – plagiarism is frowned upon. Plagiarism isn't just stealing money out of the pockets of others – this is a story about fan fiction. We don't get paid. BUT at the end of the day, many fanfics are so extensively planned, written over the course of hours, days, months, even years. And these authors are dedicated to this hobby that they provide for free. It's so important to emphasize that these people are sharing their own ideas, thoughts, wants, and passion with people.

Which is why it's so disappointing when people steal these words to pass off as their own.

Archive Of Our Own, the largest platform for sharing fanfiction on the internet, provides tools to acknowledge other creators. Some people put their inspiration as hyperlinks in their Summary section, so it appears before you even click into the work. AO3 offers a section, when you upload, to denote if you've remixed, translated, or received inspiration from another work, which many authors use! Some even put their reference to their newest works in the end notes of their fics, especially if a specific section relies heavily on the source work material.

So there's no excuse to not reference the source material. There's no excuse to not give credit to the original work of others.

I think, as a fandom, it's important to credit other authors. Not only does it help to cultivate the culture – helping others find works they might not have found otherwise - but it's just the right thing to do. If we wouldn't accept this from YouTubers, Authors, or literally any other hobbyist in the world, why would we accept it from our friends or peers in the fandom space? If it's enough to vilify someone else, why would we make excuses for the person next to us?

Recently, with the growing trend of AI and its plagiaristic uses, fandom has more and more been calling out the use of AI. It is, afterall, essentially stealing works for other people to just mishmash into something uncanny. "AI Art" get's a lot of heat and push back from fandom spaces. In fact, in the Namori fandom, there have been several instances of resistance again AI-generated fanart. Bc people inherently realize the theft and degradation of someone else's work.

I think it's important to hold ourselves to the same standard as everyone else. If we're going to bash someone for using AI or stealing art – how is fanfic different? How is it different to use a machine that steals and repurposes art, versus using your own pen? Personally, there is no difference. Because at the end of the day, we're spitting in the faces of the people who have spent countless hours, days, months, and years honing their work. Even if it's just a single line, stealing work is to say "I don't care enough about this medium to put the work in."

If you love something, and you feel passionate about it, the work necessary to create your fan or original work is something you're willing to do. For every line. If you're passionate about something, you wouldn't want to diminish it's light.

I could not, in one post, talk about every single fan author who has ever plagiarized. I could not talk about Cassandra Clare and the hundreds of other instances of plagiarism in fandom spaces bc I'm sure eventually I'd hit the word-limit. There's simply too many cases of people smearing dirt on the faces of the fandom they profess to love.

But today, I want to address for-want-of-a-nail. I want to address them because recently (aka this week) they have accused of the very thing I find so abhorrent. I want to analyze them, their response (or lack their of), and show that this isn't something that just "accidentally happens". There are conscious choices made here, that I think are in-line with what a lot of plagiarist do, especially in Fan-spaces.

For Want of a Nail

@for-want-of-a-nail has been accused of plagiarism in the Shadow & Bone community.

The Discord Sever

Last year, Nail was removed from a large Darklina Discord Sever for plagiarizing major passages and lines from another user's (Ceris_Malfoy) work that had been published in the Discord-shared Google doc before making it to AO3. Nail published their fic first, leaving the original author to debate deleting her own work due to fearing being labeled a plagiarist. The author ended up posting her full story, with no changes, but provided her statement on the matter at the end.

Nail never apologized to this creator. They never acknowledged this creator. They only said there was "inspiration" from other server members, without naming who they were.

This happened months ago. So you may wonder: "why are you bringing this up now?" I wanted to point out something that's been explored before, a notion about plagiarist that appears to ring true in this instance with Nail as well as with other plagiarist online:

The chances that someone only plagiarized once are low. The chances are, someone [like For-Want-Of-A-Nail] will have done this more than once, having rolled the dice time and time again, knowing or thinking that they wouldn't get caught.

(Paraphrased from HBomberguy's video)

I wanted to show that what occurred in the last month was not an accident, at least in my opinion. Like with Ceris_Malfoy, for-want-of-a-nail deliberately went and copied sections of text, barely adjusted it to fit her story, and refused to acknowledge or even apologize for her blatant theft of the work.

So what happened?

On January 1, 2023, @madismen posted the first chapter to Nordenfor Solen.

On December 5, 2023, for-want-of-a-nail published the 5th Chapter of Insider Threat.

It was noticed immediately by an anonymous user, who then commented on Madi's fic to reach out, bringing Madi's attention to the situation. And, of course, Madi noticed it immediately. Let's take a look from the screenshots below. (Nail has, allegedly, begun to change the original document. These screenshots were taken before Madi attempted to reach out.)

Warning for NSFW content below.

As you can see, in some places, such as when Alina/Nina are requesting panties, Nail directly copied the line without changing it at all.

To me the most damning thing is rearranging and replacing facets of the dialogue to make it not exact. A clear intent is required there. An understanding that "this thing is wrong, but I don't want to create my own dialogue, so I'll just fudge it." To me that's the part that makes this blatant theft.

Now, at this point remember, we've just gotten to the point where this is pointed out to Madismen at the beginning of this year. She attempted to reach out to For-Want-Of-A-Nail, but Madi couldn't access their Tumblr. (I believe that Nail preemptively blocked Madi on Tumblr, as many others were able to access their profile at this time.) So she left the following comment on Nail's fic.

Now, if you had clicked the link to Nail's fic, you may have noticed that this comment is not there. This is because for-want-of-a-nail deleted Madismen's comment, refusing to even acknowledge or deny the accusation at all.

Which lead to Madi posting on Twitter X about the situation. I believe both plagiarized works from for-want-of-a-nail have been reported to Ao3, but given their track-record this year I won't be holding my breath. And as of writing, that is the end of it.

for-want-of-a-nail blatantly stole someone else's work and refused to apologize and correct the situation. At least twice within the last year. Now I'm not going to go onto every chapter of every work of theirs to double check and attempt to find other instances of plagiarism. Twice is enough for me, personally, to know that they have likely done this before, and will likely do it again. In my opinion, I think that Nail is aware that what's they're doing is bad. They're aware that stealing is wrong, and that it would change the way their readers respond to the fics they post.

So What?

Speaking with other's in the Darklina community, as well as seeing how people react to other plagiarist on the internet, there's a clear line that is crossed. Consumption, especially in the Western world, is definitely connected now a days with Morals. And there is a large conversation about content vs morality and the lines you should draw from it. But, generally, a consensus has been drawn in at least one area.

Knowing that the work you're consuming is stolen, changes how you feel about it.

(Also paraphrased from HBomberguy, who put it much better than me.)

The worst part of all of this, to me, is the betrayal to readers. To those who genuinely enjoy the works being published and thinking that they are following someone who is creative and passionate about the subject they are writing. Only for them to be lied to. Because yes, when Nail responds to comments gushing over the work as if they wrote every single thing by themselves, they are lying to people.

They felt so entitled to Madismen's words, while going out of their way to call those invested in their story entitled for wanting more.

I think, personally, this is just someone who thinks of fandom as a competition. Someone who is willing to lie, steal, and belittle any and everyone who isn't them. It's not what fandom is supposed to be about. Fandom is a community of people who come together to share and expand their thoughts and feelings about any property. Nail essentially went to Show and Tell, smacked someone else's story out of their hand, then held it up as their own.

Where do we go from here?

Now, like I said at the beginning of this post, I don't want anyone to go out and harass this person. I don't want anyone to bully them, or make us come out and defend them.

Just ignore them.

Madismen has said her piece. I've just chronicled it. We don't need to attack or bully this person, but now that we are aware, we don't need to give them any attention. Giving Nail attention lets them think they've won. It would normalize their actions. We don't have to do either of those things. We don't have to acknowledge someone who has proven they don't care about the people in their fandom. We don't have to do anything.

The great thing about internet fandom is that we can choose who to follow and engage with. We can choose to consume fics that we love, written by people who didn't steal their words. You wouldn't read a plagiarized book. Or at least you shouldn't, because then you're supporting someone who has stolen wages on top of an idea.

There are thousands of works on AO3. There will be another one to read.

I don't want a witch hunt. I want people to stop stealing from other people. But, as I know that won't be happening, I think it's better to call out and learn to avoid these people. Like with the James Somerton situation (aka the HBomberguy video), I think it best that we just don't support this kind of behavior. Yes I'm on my soapbox a little, but it's also my blog and my personal opinion on the matter. Everyone is entitled to their opinion, but please, don't go harassing these people, especially Nail. Just let them find out the consequences of their actions naturally.

[arabella-strange]

Harbour (Day 28) — Citations

Because I got too wordy for AO3's endnote character max....

References (continuing from Days 26–27):

Re-upping a strong rec for all things radical reform & rebellion in the 1810s-20s: E.P. Thompson's Making of the English Working Class. Interesting how much of Luddite history and uprisings were indeed in Nottingham(shire), Glasgow, and London. We love to see it.

As for Days 26–27, here I'm also relying on those records about the real Crown & Anchor (see prev. citations).

TBH I did a speedrun through the entire Black Sails series, and in my head, Tharkay's world pre-Temeraire was basically Black Sails 85 years later. His experience of Macao might as well be the Anglo-Chinese Nassau: the cutthroat tactics, the deeply suspicious individual cunning, the sudden swerves of loyalties, the layers upon layers of private goals and ambitions, the way that even your teammates and lovers and most trusted friends could kill you any minute? (Plus the hatred of the hypocrisies of empire and the follies of short-sighted men?) That's what it was like for (my) Tharkay. S/o Lt. James McGraw—know no shame.

Austen stayed on Henrietta Street in London, and Austen is always nearby when I'm writing this fic, esp. for dialogue, because why would you go anywhere else for dialogue or free indirect narration.

The Bengali dragons (who sadly in the final draft don't appear onstage) come from the canon scene in League of Dragons [pp.185—190]. I also imagined my Priya Ghuri as a Himalayan dragon (breed Pālaka Cilla, from the Sanskrit words for 'protector/shield' and 'kite/sky'): imagine something like a much more draconic Falkor, white-scaled, reptilian, fanged, but also yeti-furry to survive the alpine climate of the Himalayas, and very rare if not fully legendary (thus part of Tenzing's childhood tales).

In the period around 1817, the northern parts of the Indian subcontinent were often in revolt against British (in this period meaning East India Company) rule. This includes the Second and Third Anglo-Maratha War, plus the Anglo-Nepalese War (Treaty of Sugauli, 1816). Coverage of these wars and praise for the then-Governor-General of India, the Marquess of Hastings, showed up in the Times of London and in parliamentary debates around early Feb. 1817.

Map of the streets of London (1815) — so high-def and gorgeous: UW Milwaukee ily.

Maps of British India, 1765 vs. 1805, indicating 'Ceded and Conquered Provinces,' from Harvard. Another map of India from 1805 (wiki). 

Menu for an average (genteel) winter dinner party from Cookery and Confectionary (1824) by John Conrade Cooke via the Wellcome Collection.

Even though the real 'London club-land' vibe didn't get into full swing until the mid- to late-Victorian period, there were certainly gentlemen's clubs and dining societies for Georgians. I also borrowed (proleptically) some enormous paintings for their walls — like Lear's Mount Kanchenjunga from Darjeeling(1877) — and just, as it were, imagined dragons.

I finally gave Tenzing's mother a name. Because Tenzing is — in my story — Nepali by heritage, and that region was complicated by British rule/intervention for the generation+ before Tenzing's birth, I think his mother would today be Nepali but with more Tibetan rather than Indian or Chinese heritage. So 'Baskota Dawa Tharkay': Baskota is a common Nepali surname (and I think I am right that common usage styles Nepali names with surname/family name first, given/first name second); Dawa is a given name across several Himalayan societies, meaning 'moon,' also 'Monday,' as a marker of an ancestral Tibetan/Buddhist lifeway. 

Lastly (for now), the lantern that Tenzing buys for Tem. in Belgium (not that there was a 'Belgium' in 1817) is based on this stained glass lantern which borrowed reconstructed much older pieces of glass into a new Gothic art object for Strawberry Hill. It's big. My friend did her diss on c19 repurposing of older stained glass, including how novel and rapidly evolving techniques for modern glass manufacturing sometimes overlapped with glaziers and antique dealers who took advantage of the dismantling of many European churches around Napoleon, selling off segments of ancient or medieval glass. But there's another fic in that to come…

[fic here]

[worldseo123service]

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[miskinmusic24-25]

You will have noticed that the last part of your Project Proposal is titled ‘Proposed Research Sources & Bibliography (Harvard Format)’

In this section I need you to list the types of research you have already been using as well as those you anticipate using during the project.

Also I would like you to demonstrate here that you know how to use the Harvard system so that you can use it for every piece of research that you put onto your WIX site

Why do we need to do this?

There are many reasons but the main two are:

Firstly it will help you to avoid accusations of plagiarism. So that you can include other peoples work on your site and be clear about what opinions are your own.

Secondly as we use so much research these days from Internet sites, we need to show when we accessed the information because the person in control of the content could change it at any time.

Start by posting the first piece of secondary research from your research tab and include the Harvard Reference below it.

Below this post is an example from my own Youtube channel

Above is a link to a website called Neil’s toolbox, that will build your references for you. If you were referencing a Youtube video for example, you click on ‘referencing a website’ and simply fill in the information in the boxes below.

Author will be who’s channel it is

Article Title will be the name of the video

Name of Website will be Youtube

Below is an example:

[lovingthelooking]

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🔥 Ready to Ace It? These tips will keep your CIPD assignments error-free and assessor-approved. Got a mistake-avoiding hack? Drop it in the replies or DM us! Reblog if this helped, and follow for more CIPD vibes. Need pro support? Hit up CIPD Assignment Help for flawless assignments. ✨

[kevin4569]

Plagiarism-Free Management Assignment Help Australia: Ensuring Academic Success

Academic integrity is the cornerstone of higher education, and students are expected to submit original work that reflects their knowledge and understanding. However, managing complex assignments while juggling multiple responsibilities can be overwhelming. This is where Management Assignment Help Australia comes into play, offering students expert guidance while ensuring plagiarism-free solutions.

In today’s academic landscape, universities have stringent policies regarding plagiarism, and students must adhere to ethical writing standards. Seeking professional assistance is not just about getting the work done but also about learning, improving skills, and maintaining academic honesty. Let’s explore how reliable Assessment Help services can support students in achieving their academic goals while maintaining originality.

The Importance of Plagiarism-Free Management Assignment Help Australia

In the field of business and management, assignments require critical thinking, analysis, and real-world application of theories. Many students struggle with structuring their responses and providing well-researched arguments, leading them to unintentionally commit plagiarism.

Professional Management Assignment Help Australia services ensure that assignments are written from scratch, tailored to individual requirements, and backed by credible sources. These services emphasize uniqueness by using advanced plagiarism-detection tools and following proper citation guidelines. By availing such help, students can submit original work while deepening their understanding of the subject.

Furthermore, many students are unaware of how to paraphrase or reference properly, which increases the risk of unintentional plagiarism. Reliable Assessment Help providers not only deliver quality content but also educate students on academic integrity, citation techniques, and research methodologies.

Why Choose Professional Assessment Help?

When faced with complex business and management assignments, students may feel overwhelmed by the amount of research required. Professional Assessment Help services offer a structured approach to tackling assignments while maintaining originality.

1. Expertise from Qualified Professionals

Leading academic help providers have a team of subject matter experts who possess extensive knowledge in various management disciplines. These experts conduct in-depth research and provide insights based on real-world business scenarios. Unlike generic content found online, expert-written assignments offer original perspectives that enhance the quality of submissions.

2. Customized Solutions for Unique Needs

Every assignment has specific requirements, including case study analyses, theoretical applications, and strategic decision-making. Professional services deliver Management Assignment Help that is customized to meet university guidelines, ensuring that no two assignments are identical.

3. Advanced Plagiarism Detection Tools

To ensure authenticity, assignments go through rigorous plagiarism checks using tools like Turnitin, Grammarly, and Copyscape. This guarantees that the final document is 100% original and free from any form of duplication.

4. Proper Referencing and Citation Techniques

One of the primary causes of plagiarism is improper citation. Management assignments often require references from journals, business reports, and industry publications. Professional services ensure accurate citation in various formats, such as APA, Harvard, and MLA, helping students maintain academic credibility.

How Management Assignment Help Promotes Academic Integrity

Academic institutions across Australia emphasize ethical writing practices, and students must comply with these standards. Seeking Management Assignment Help does not mean compromising on integrity; rather, it is a learning opportunity to enhance research and writing skills.

1. Learning the Art of Original Writing

Many students struggle with writing in their own words, especially when dealing with complex theories. By reviewing well-structured assignments from professionals, students can learn effective paraphrasing techniques and develop their unique writing style.

2. Encouraging Critical Thinking and Analysis

Expert-written assignments demonstrate how to analyze business problems, interpret data, and develop well-structured arguments. This helps students improve their analytical skills, which are essential for academic and professional success.

3. Avoiding Common Pitfalls in Assignment Writing

Plagiarism often occurs due to last-minute submissions and poor time management. By seeking timely Assessment Help, students can plan their assignments better and focus on learning rather than copying existing content.

4. Enhancing Research and Data Interpretation Skills

Management assignments often require students to use real-world data and case studies. Professional assistance teaches students how to conduct research, interpret data, and present findings in an original and structured manner.

Ensuring Quality and Originality in Management Assignments

A high-quality management assignment is not just about avoiding plagiarism; it should reflect a well-researched and logically structured approach. The best Management Assignment Help Australia services follow a systematic process to ensure top-quality work.

1. Thorough Topic Research

Experts conduct in-depth research using credible sources such as business journals, government reports, and case studies. This ensures that the assignment is rich in relevant data and supports logical arguments.

2. Unique Content Development

Every assignment is written from scratch, focusing on the unique requirements provided by the student. This eliminates any possibility of duplication or recycled content.

3. Comprehensive Proofreading and Editing

Editing and proofreading play a vital role in maintaining quality. Professional services have dedicated editors who review assignments for grammatical errors, coherence, and overall clarity, ensuring that the final document is polished and professional.

4. Plagiarism Check and Report Submission

Reputed academic assistance services provide plagiarism reports along with assignments, giving students confidence that their work is original and meets university standards.

The Role of Management Assignment Help in Academic Success

University students in Australia face increasing academic pressure due to tight deadlines, complex coursework, and evolving business concepts. With the help of Management Assignment Help, students can stay ahead in their studies while ensuring compliance with academic integrity policies.

1. Meeting Deadlines Without Compromising Quality

Timely submission of assignments is crucial for academic success. Professional services deliver well-researched assignments within deadlines, allowing students to focus on other academic responsibilities.

2. Gaining a Competitive Edge

High-quality assignments contribute to better grades, which play a crucial role in academic achievements and career opportunities. A well-researched, plagiarism-free assignment demonstrates a student’s ability to think critically and apply management concepts effectively.

3. Stress-Free Academic Experience

Balancing studies, part-time jobs, and personal commitments can be challenging. Seeking professional Assessment Help allows students to manage their workload efficiently while maintaining a healthy academic-life balance.

4. Long-Term Learning and Skill Development

Beyond immediate academic benefits, professional assignment assistance helps students develop research, writing, and analytical skills that will be valuable in their careers.

Final Thoughts: Choose Plagiarism-Free Management Assignment Help Australia

Maintaining academic integrity is non-negotiable in higher education. By choosing professional Management Assignment Help Australia, students can ensure plagiarism-free, high-quality assignments that enhance their learning experience. Reliable services not only provide expert guidance but also equip students with essential research and writing skills.

Whether struggling with complex management theories, case study analysis, or strategic decision-making assignments, students can benefit from tailored Assessment Help that aligns with university standards. By prioritizing originality, professionalism, and academic growth, students can confidently achieve their academic goals without compromising on integrity.

For students looking for ethical, reliable, and plagiarism-free assistance, professional Management Assignment Help services in Australia offer the perfect solution to academic success.

[da-fmp-y1]

Harvard format

just putting a note to make sure I remember how to convert links to Harvard format

[thetutorshelpuk]

Bond University Assignment Help

Bond University is a prominent private Australian university, which is renowned for its quality academic standards, teaching pedagogy, and excellent student facilities. Students studying their courses from Bond University need to finish different assignments, research reports, case studies, and projects as course work. The assignments help the students refine their critical thinking, analytical reasoning, and subject matter knowledge. But at times it is difficult to finish them due to strict deadlines, technical content, and academic pressure. That is where The Tutors Help comes into play to provide quality assistance in your Bond University assignments.

Why Assignments Matter at Bond University?

Assignments are a component of the curriculum at Bond University. Assignments help students:

Grasp Concepts Better: Reading and writing assignments improve comprehension of the topic.

Enhance Research and Writing Skills: Academic assignments enhance better research and analytical skills.

Enhance Grades: Well-written assignments enhance overall academic marks.

Enhance Careers in the Future: Assignments are more of real application, hence students are ready for industry.

But as most students have a time limit, lack proper resources, or cannot grasp some concepts, they are unable to do their assignments.

Assignment Writing Problems Confronted by Students

Time Management Issues: With assignments, tests, and extracurricular activities, students generally have trouble with deadlines.

Tough Subjects: Certain subjects require deep knowledge and extensive research work, so it becomes hard to manage the assignments.

Lack of Research Ability: Most students are not aware of where they can gather proper and genuine information for their assignments.

Plagiarism Issues: Universities hate plagiarism totally, and 100% original student work is always expected.

Formatting and Referencing: Assignments need to be well-referenced (APA, Harvard, MLA, etc.), and this will put the students in a dilemma state.

How The Tutors Help Helps Bond University Students

We at The Tutors Help provide professional assignment assistance to Bond University students for a variety of courses. Here's how we can help you:

1. Subject Experts

We possess subject matter experts who are well-experienced with academic writing, and we assure quality assignments.

2. Personalized Solutions

We provide customized assignments as per your university needs and requirements.

3. 100% Original and Non-Plagiarized

Our assignments are 100% original and have proper references and citations for authenticity.

4. Timely Delivery

We understand the importance of deadlines and submit your assignments well in advance.

5. Affordable Pricing

Our services are competitively priced so that expert assistance is available to all students.

How to Get Assignment Help from The Tutors Help

Submit Your Assignment Details: Let us know your topic, guidelines, and deadline.

Get a Quote: We quote you a fair price for the service.

Receive Expert Assistance: Our experts begin working on your assignment immediately.

Review and Submit: Receive your completed assignment, check it, and submit it confidently.

Final Thoughts

Bond University students typically have to complete their assignments within given deadlines owing to academic pressure and time constraint. The Tutors Help guarantees quality support and production of quality, well-researched, and plagiarized-free assignments.

We welcome you to contact us at The Tutors Help anytime you desire quality assignment services from our experienced professionals. We can give assurance of academic success with us!

[houseofassignment]

How to Choose the Right Referencing Style for Your Academic Assignments

Hey, emerging minds out there, if you're a student in Australia, chances are you've come across different referencing styles while working on your assignments. Whether you’re writing an essay, research paper, or report, using the correct referencing style is crucial. But with so many styles out there—APA, Harvard, MLA, Chicago—it can be confusing to figure out which one to use.

If you’ve ever thought, “I need to write my assignment Australia style, but which referencing format should I follow?”—this guide is for you! We’ll break it down in simple terms so you can pick the right style with confidence.

Here are the key factors to consider when selecting the right referencing style for your assignments:

1. Check University Guidelines

Most universities in Australia have specific guidelines on which referencing style to use for different subjects. Always refer to your assignment brief, course handbook, or university website to confirm the required style. Using the correct format as per university standards ensures you don’t lose marks due to incorrect citations.

2. Know Your Subject Requirements

It is important to know what exactly is required. Different academic disciplines prefer specific referencing styles. Understanding your subject’s requirements helps you use the correct citation format. Below are commonly used styles for different subjects:

1. APA (American Psychological Association)

This referencing style is commonly used in Psychology, Social Sciences, Education, and Business. It follows an author-date format, making it easy to track sources. Example: (Smith, 2023).

2. Harvard Referencing

It is widely used in Business, Economics, Management, and Humanities. Similar to APA, but has slight variations in punctuation and formatting.

3. MLA (Modern Language Association)

It is Preferred in Literature, Arts, and Humanities. Uses in-text citations with the author’s name and page number (Smith 45) and a Works Cited page.

4. Chicago Referencing

It is often used in History, Law, and Fine Arts. Has two versions: Notes and Bibliography (for humanities) and Author-Date (for sciences and social sciences).

5. IEEE (Institute of Electrical and Electronics Engineers)

It is common in Engineering, Computer Science, and IT. Uses numbered citations in square brackets [1], with a corresponding reference list.

Selecting the right style based on your subject ensures clarity and adherence to academic standards.

3. Ask Your Professor or Tutor

If your assignment instructions don’t specify a referencing style, or if you’re unsure which one to use, consult your professor or tutor. They can guide you on the appropriate format based on academic expectations and research conventions. This step can prevent unnecessary corrections and rework later.

4. Take Help of Online Citation Tools

Manually formatting references can be time-consuming and prone to errors. Fortunately, various citation tools can help you generate accurate references in different styles. Some popular tools include:

Zotero – A free tool that helps organise research sources and create citations.

EndNote – A widely used software for managing references and creating bibliographies.

Citation Machine – A web-based tool that provides instant citations in multiple styles.

Mendeley – Assists with citation management and collaboration in research.

These tools not only save time but also ensure accuracy in your citations and references.

5. Try Stay Consistent

Using multiple referencing styles in the same document can create confusion and make your assignment look unprofessional. Once you select a referencing style, stick to it consistently throughout your assignment. Consistency applies to:

In-text citations

Reference list formatting

Capitalisation and punctuation rules

Placement of page numbers and author details

Staying consistent enhances readability and demonstrates your attention to detail, which can positively impact your grades.

Why Is Referencing Important?

Before we dive into the different styles, let’s first understand why referencing is such a big deal:

Avoids Plagiarism: Proper citation gives credit to the original authors and helps you avoid academic misconduct.

Builds Credibility: A well-referenced assignment shows that you’ve done thorough research.

Helps Readers Find Sources: Referencing allows others to track down your sources for further study.

Now, let’s explore the most common referencing styles used in Australian universities.

Who Can Help You?

Well, at House of Assignments, we have expert writers who have years of experience in every subject and reference writing style. You can connect us if you want someone to write my assignment Australia. We are here to help you with 100% original, 100% plagiarism and high-quality assignment service before the deadlines. Join us and increase your chances to improve your grades.

Conclusion

Using the right referencing style is very important for academic integrity, proper citation, and structured writing. Following university guidelines, understanding subject-specific requirements, consulting your professor, utilising citation tools, and maintaining consistency will help you master referencing effortlessly.

So, next time you work on an assignment, remember these key factors and ensure your citations are on point!

[fiercestpurpose]

“Ivy League” has a precise definition. It refers to the following eight (8) universities:

Brown

Columbia

Cornell

Dartmouth

Harvard

Princeton

UPenn

Yale

If it’s not one of these eight (8) schools, it’s not an Ivy. Ivy League schools are prestigious, wealthy, highly-ranked universities. That does not mean that every prestigious, wealthy, highly-ranked university is an Ivy.

This matters ONLY because I like it when terms are precisely defined. This is not an endorsement of the colleges or of the culture around these colleges. This is definitely not me saying that if it’s not on the list, it’s a bad school.

(My general philosophy on choosing colleges, which is not really relevant to this post but which I will share anyway, is that fit is much more important than rankings. Do they have opportunities you want to take advantage of? Do they offer programs that appeal to you? Are the campus culture and the city the school is in going to work for you? How much money are they offering and can you get out of college debt free?)

[sidraseoiyh]

10 Best AI Tools for Students in 2025

Being a student in 2025 means juggling endless assignments, research, and deadlines. Thankfully, AI tools are here to make life easier. From automating research to improving productivity, these tools can save you time and help you work smarter. In this blog, we’ll explore the 10 best AI tools for students in 2025, including one standout tool that’s revolutionizing the way students handle research.

1. ResearchPal

Research is a core part of student life, but it can be overwhelming. ResearchPal simplifies the process by automating your research workflow. It helps you find, summarize, and organize sources efficiently, with free access to powerful language models for generating insights and drafting content.

What makes ResearchPal unique is its adoption by top universities worldwide, including Harvard University and Stanford University. It’s a trusted tool for students and academics alike.

2. Gradescope

Gradescope uses AI to streamline grading and feedback for assignments and exams. It’s widely used in universities like UC Berkeley to help instructors provide detailed feedback quickly, saving time for both students and teachers.

3. Wolfram Alpha

Wolfram Alpha is a computational knowledge engine that helps students solve complex math, science, and engineering problems. It’s a go-to tool for students at institutions like MIT who need quick, accurate answers.

4. Zotero

Zotero is a free, open-source tool for managing research references and citations. Its AI features help you organize your library, suggest related papers, and generate citations in various formats. It’s a favorite among researchers worldwide.

5. Anki

Anki uses AI-powered spaced repetition to help students memorize information more effectively. Whether you’re learning a new language or studying for exams, Anki’s smart algorithms ensure you retain information long-term.

6. Copyscape

Copyscape is an AI tool that helps students check their work for plagiarism. It’s essential for ensuring academic integrity and is widely used by universities like Oxford University.

7. Speechify

Speechify is a text-to-speech tool that uses AI to convert written content into audio. It’s perfect for students who want to listen to textbooks, articles, or notes while on the go.

8. DeepL Translator

DeepL Translator is an AI-powered translation tool that provides accurate, natural-sounding translations. It’s ideal for students studying foreign languages or working with international research material.

9. Hemingway Editor

Hemingway Editor uses AI to improve your writing by highlighting complex sentences, passive voice, and readability issues. It’s a great tool for polishing essays and reports.

10. MyScript Nebo

MyScript Nebo is an AI-powered note-taking app that converts handwritten notes into digital text. It’s perfect for students who prefer writing by hand but want the convenience of digital organization.

Why ResearchPal Stands Out

While all these tools are incredibly useful, ResearchPal stands out for its focus on research. It’s not just about saving time—it’s about making the research process more efficient and less stressful. By automating tasks like summarizing papers and organizing sources, it allows you to focus on analysis and creativity.

What’s more, ResearchPal’s free access to large language models means you don’t have to compromise on quality, even if you’re on a budget. Its adoption by top universities like Cambridge University and Yale University is a testament to its effectiveness and reliability.

Final Thoughts

AI tools are transforming the way students learn and work. Whether you’re researching, writing, or studying, these 10 tools can save you time and boost your productivity.

Start with ResearchPal—explore its features, see how it’s used at top universities, or check out the pricing to get started for free.

And don’t forget to explore other tools like Gradescope, Wolfram Alpha, and Zotero to find the combination that works best for you. The future of learning is here—why not make the most of it?

Here’s to smarter studying and greater success in 2025!

[oaktaro]

PC Horror Games in 1979

By the 1970’s, the horror game genre spanned across all major platforms, from 2 generations of home consoles to arcades to desktop and mainframe computers. Commercial general-purpose digital computers that can store programs and games for them had been around since at least the early 1950’s. The 60’s advertised compact and affordable minicomputers, and, in the 1970’s, surged in popularity in what is referred to as “the microcomputer revolution” after a 1968 breakthrough resulted in things becoming even tinier and soon more affordable. Alongside them, commercial video games (which had arguably also been on the market since, at least, the 1950’s) had finally become mainstream, which is a phrase that almost gives me PTSD with how annoying people used to be about it, but by the 1970's, video games were mainstream entertainment, so large that within just 3 more years, they would be considered bigger than Hollywood and pop music COMBINED! You can imagine, by the 70’s, home computers were already made with developers in mind. For the average Joe simply wanting to play horror games in the 1970’s, consoles being streamlined home and portable personal computers made for that purpose would be the way to go, which is probably why so many did, and that history is often celebrated, but I’m curious about the landscape of the desktop PCs. I’d like to take a look at this microcomputer revolution from the perspective of its horror games.

Microsoft

This “revolution” is often attributed as starting in the early 1970's, where Lakeside high school students Paul Allen and Bill Gates commonly sought access to computers, even being banned from seemingly more than one place like Computer Center Corporation, where they exploited a bug to get additional free computer time. They would form the Lakeside Programmers Club to make money working with computers, including for the center that banned them! After high school, they’d go to different colleges, and Paul Allen would drop out to become a programmer for Honeywell. A week before Christmas of 1974, a new issue of Popular Electronics would drop, showcasing a new player in the microcomputer game, the Altair 8800, using the new Intel 8080, whose predecessor, Paul and Bill, worked with in their younger years. Inspired to start his own software company, he would contact the computer maker about software and convince Bill Gates to drop out of Harvard and join him in making an interpreter for BASIC programming language to run on it, forming Microsoft. Paul flew out to deliver what they made and showcased it by playing some version of the 1969 game Lunar Lander.

Kadath- 1979 July 15 – Altair 8800

The 8800 would become a popular PC to the point of being credited as the start of desktops leap in popularity during the 1970s, which is what people refer to as the “revolution” as opposed to the 1968 breakthrough itself, and, on July 15th of 1979, a horror game would be written for it. A fan fiction set in the world of the works of famous Rhode Island author, Howard Philips Lovecraft. Kadath tells the story of said world Yaddith being in danger of the return of a precursor civilization, whom a stone tablet you find on an archaeological dig prophesies will return when the stars align correctly. You have set out to find the eye of Kadath, a gem thought to be powerful enough to destroy the gateway from which they would enter, which you plan to do by cracking open the eye to unleash its power. Kadath framed its writing seriously and had content I found more visceral than previous games of its genre. Despite infamous typos, I found it well written, though it’s not my taste in horror. Gameplay, however, I found to be an improvement through its use of multiple-choice actions instead of making the player figure out what to type. Depending on how you feel about text adventures, you might find this to be a downgrade, or if you find figuring out what to type in a text adventure a horror in itself, you might see it as a relief. This game would also not remain exclusive to the 8800 and be brought to future home desktops.

Apple

When a now famous hacker by the name of Steve Wozniak was working at Hewlett-Packard, his friend told him he should meet a high school student by the name of Steve Jobs who likes electronics and playing pranks. At the time, Wozniak was inspired by an article in Esquire magazine about blue boxes that emulated the sounds phones make to connect people, therefore allowing you to hack free calls. He wanted to make his own, and Jobs wanted to sell it. Selling them for $150 each, splitting the profits—this would be the dynamic people remember of “the 2 Steves”: Woz knows how to make the tech and Jobs knows how to sell it. What I always remember though is how Jobs believed his vegetarian diet ensured he wouldn’t produce body odor and thus he wouldn’t have to shower, which his coworkers at Atari didn’t seem to agree with, causing them to quickly put him on the night shift, which didn’t exist, meaning he’d come into the building when everyone was gone and be able to bring Wozniak in to get things done. His boss, Nolan Bushnel, was aware but didn’t really care because, as he put it, he got “two Steves for the price of one" He did offer Wozniak at least one bonus, but through Jobs, who hid it from him. Woz would eventually make a computer for his homebrew computer club, and after his workplace was uninterested in buying it from him, Jobs would convince him they should start their own company and sell it themselves. After this 1976 referred to as the Apple 1 would find good success, the Apple II the following year would become sought after by aspiring video game developers as a desktop made for making video games. It shipped with an interpreter made with hobbyists and game devs in mind that allowed users to immediately write software without additional stuff needed.

Akalabeth: World of Doom – 1979-1980 – eventually Apple II

Now dawn your thinking beard for this one. A question I’ve pondered is the Venn diagram of considering something in the stereotypical old European fantasy setting and something being considered a horror game because there are a lot of games like 1979’s Dungeon of Death which are considered to be horror games that I never would have thought of as horror games. I’m curious what percentage of people consider which of these to be horror games from that first-person dungeon crawler Puyo spawned off from to Baldur’s Gate or Untold Legends. There’s no wrong answer to me. I just notice it’s a far higher percentage than I thought. I bring all this up because one of the people to make games for the Apple II was soon to be famed Ultima creator Richard Garriott, just 2 years before Ultima. It apparently started as a high school project he made on a school computer, which was one of 28 fantasy games he made in high school before getting his hands on an Apple II and making the more fleshed-out version, Akalabeth: World of Doom, and I can see how its cover sets a tone that carries over into the first-person dungeon crawler featuring hooded figures and the general tension of running into danger while exploring, especially in a first-person game. Picture Zelda 2, where there’s a top-down overworld and sidescrolling dungeons. This is like that where there’s a top-down world to explore with towns and mountains while dungeons are explored in first person, which was inspired by the 1978 game Escape. The worlds are randomly generated, asking you for a world seed so you can always get the same world if you use the same seed, technically meaning you can collaborate with other players by sharing knowledge as you learn specific worlds. The game takes place in the aftermath of British, the bearer of white light, having driven off the dark lord, Mondain, who spread evil to the land. Now, arguably, you don’t have to, but the game recommends you search for the castle of Lord British, who will task you with slaying various monsters located in these dungeons that are remnants of the dark lord. Apparently Richard Garriott was working at ComputerLand at the time, which was a computer store chain in the 1970’s, and showed the game to his boss, who told him they should sell it in the store! He had his mother draw a logo to sell the game in Ziploc bags, which is the version of packaging I like to see, but it eventually got the attention of California Pacific, who contacted him, wanting to publish it professionally.

Commodore

Back in 1975, electronics company Commodore was beginning to run into a concerning situation when, to compete with the lowering prices of calculators, Texas Instruments entered the market themselves, antiquating those they sold chipsets to like Commodore. Realizing the calculator game was over for them, they would attempt to jump onto the hype of the desktop side of the microcomputer revolution and look to the Apple II to sell. They considered Steve Jobs offer too expensive and decided to make their own computer! The Commodore PET was named after the 1975 Pet Rock craze for their goal of making a pet computer. Despite being sighted as releasing in January of 1977, this seems to only be the date of a Consumer Electronics Show appearance it made after it’s 1976 announcement, but perhaps people could start placing orders at this point. Whenever orders could start being placed, they’d be sent out in late ‘77, starting with developers and magazines in October like Byte, who would later be credited with referring to it as part of their famous trinity of 1977 desktops alongside the Apple II and Tandy-RadioShack Z-80. While all 3 of these computers licensed Microsoft BASIC, having one video game run across all of them did not seem so basic. Ports for games can be years apart, sometimes changing game content and even names like the Commodore version of Kadath, Eye of Kadath, seemingly being far more abridged. I’ve seen some people prefer the more condensed Eye of Kadath, and there can be a strength to the short and sweet format.

Haunted House – 1979 – Apple II

A common name for a game which wants you to escape said Haunted House by midnight but it’s full of so much danger that you may find yourself trying new things across multiple playthroughs with your eye also on the clock ticking down on the clock ticking down to midnight assuring runs don’t last too long even if you avoid the densely packed danger. It encourages a form of running the game in short, sweet, trial and error attempts to make it easier to approach and just try again on a different day with short play sessions alleviating a bit of concern for how much time you have to set aside. Its writing style is brief, expecting to be repeated instead of approaching writing more like a horror novel as Kadath does.

There is also what I find to be a middle ground to these 2 writing styles in a series that has stood the test of time as fondly looked upon desktop games of the era.

Voodoo Castle – 1979 – Commodore PET, Exidy Sorcerer, TRS-80

Scott Adams had been making computer games since the 1960’s and, as early as 1975, was working on home computers. In ‘78, he would make a game called Adventureland that would find success, and the following year, he and his wife Alexis would found Adventure International, continuing to make these games. Number 4 in the series would be Voodoo Castle, dedicated to all moms and solely credited to Alexis Adams, though Scott, as early as 1981, saying they both worked on it, contrasting with Alexis’s wording in a ‘98 email, has led to a mini-drama over proper credit. The game itself is about you attempting to rescue Count Cristo from the slumber result of the voodoo curse his enemies hexed him with. You begin in a room with Cristo laying in a casket. From here you can explore the residence, which I assume to be the count's, as you can run into a maid who doesn’t seem to fear you as an intruder, leading me to believe you are someone who knows the count looking for something in his spooky dwelling to break the curse. This game is not too tense, but there is the fear of comically being your own undoing, like trying to experiment with the lab chemicals and they blow up in your face or simply examining an open cell in the dungeon and the door closes behind you, accidentally trapping yourself! I can see the appeal of having a simple spooky-themed puzzler like this but was truly surprised by how much I enjoyed it. Something that always stuck in my mind is Tim Schafer remarking how Sandover Village in the first Jak feels like a real town where people live, which creates an effect of dreaming or thinking about wanting to go back and hang out there when you’re not playing the game. It made me realize the deliberateness of making a world capable of building a relationship akin to a hometown with the player as opposed to just being a setting you happen to develop nostalgia for after playing a lot of the game. After only my first time playing Voodoo Castle, I’ve been having that feeling Schafer was talking about, thinking about seeing into the chapel from the room to the south or how I imagined it because I played the text-only version of the game with the environments leaving that positive of an impression on me, but I think what really makes this game work for me is that the word limit for typing a sentence is 2 words. I can’t tell you how intimidated I am by text adventure games, but simplifying it to that makes it very approachable, at least to start off with and explore around without being immediately scared off.

The Count – 1979 - Commodore PET, Exidy Sorcerer, TRS-80

The next game number in the advertised Adventure International series would have you on the other side of a count with you attempting to defeat Count Dracula. After awaking in a bed in Transylvania, you must survive days trying to remain un-hunted by Dracula to hunt him yourself. This game of predator vs. predator felt very tense to me. There can be a spy vs. spy tension of trying to sleep in fear that he’ll get you over night, you being robbed, or even Dracula finding out what you plan to use against him. A 1981 review for this game in Space Gamer magazine mentions using a tent stake as a weapon, but it’s far from as simple as running at the supernatural being. It’s a puzzle game with the added element of having this supernatural wumpus somewhere in the castle, outsmarting you to make you his prey in an instant as you try to do the same back. I may not like puzzle games, but this is a cool idea.

Adventure International opened my mind to text adventures

I used to be too intimidated by the fear of obtuseness to play these kind of games, and, while I may still prefer an action list like Kadath, the illusion of seemingly infinite possibility of just being asked “What do you want to do?” with a text box, including the satisfaction of being surprised when something you type as a joke works, is not lost on me. Simpler games, of course, make it more approachable, and I can imagine the bang for your buck of thinking about a way to progress in the game and coming back to it for a long time, trying to make progress without losing interest in the novelty of doing it on your versatile machine that you want to play with.

[techahead-software-blog]

What is AI-Ready Data? How to Get Your There?

Data powers AI systems, enabling them to generate insights, predict outcomes, and transform decision-making. However, AI’s impact hinges on the quality and readiness of the data it consumes. A recent Harvard Business Review report reveals a troubling trend: approximately 80% of AI projects fail, largely due to poor data quality, irrelevant data, and a lack of understanding of AI-specific data requirements.

As AI technologies are projected to contribute up to $15.7 trillion to the global economy by 2030, the emphasis on AI-ready data is more urgent than ever. Investing in data readiness is not merely technical; it’s a strategic priority that shapes AI’s effectiveness and a company’s competitive edge in today’s data-driven landscape.

(Source: Statista)

Achieving AI-ready data requires addressing identified gaps by building strong data management practices, prioritizing data quality enhancements, and using technology to streamline integration and processing. By proactively tackling these issues, organizations can significantly improve data readiness, minimize AI project risks, and unlock AI’s full potential to fuel innovation and growth.

In this article, we’ll explore what constitutes AI-ready data and why it is vital for effective AI deployment. We will also examine the primary obstacles to data readiness, the characteristics that define AI-ready data, and the practices for data preparation. Furthermore, well discuss how to align data with specific use-case requirements. By understanding these elements, businesses can ensure their data is not only AI-ready but optimized to deliver substantial value.

Key Takeaways:

AI-ready data is essential for maximizing the efficiency and impact of AI applications, as it ensures data quality, structure, and contextual relevance.

Achieving AI-ready data requires addressing data quality, completeness, and consistency, which ultimately enhances model accuracy and decision-making.

AI-ready data enables faster, more reliable AI deployment, reducing time-to-market and increasing operational agility across industries.

Building AI-ready data involves steps like cataloging relevant datasets, assessing data quality, consolidating data sources, and implementing governance frameworks.

AI-ready data aligns with future technologies like generative AI, positioning businesses to adapt to advancements and leverage scalable, next-generation solutions.

What is AI-Ready Data?

AI-ready data refers to data that is meticulously prepared, organized, and structured for optimized use in artificial intelligence applications. This concept goes beyond simply accumulating large data volumes; it demands data that is accurate, relevant, and formatted specifically for AI processes. With AI-ready data, every element is curated for compatibility with AI algorithms, ensuring data can be swiftly analyzed and interpreted.

High quality: AI-ready data is accurate, complete, and free from inconsistencies. These factors ensure that AI algorithms function without bias or error.

Relevant Structure: It is organized according to the AI model’s needs, ensuring seamless integration and enhancing processing efficiency.

Contextual Value: Data must provide contextual depth, allowing AI systems to extract and interpret meaningful insights tailored to specific use cases.

In essence, AI-ready data isn’t abundant, it’s purposefully refined to empower AI-driven solutions and insights.

Key Characteristics of AI-Ready Data

High Quality

For data to be truly AI-ready, it must demonstrate high quality across all metrics—accuracy, consistency, and reliability. High-quality data minimizes risks, such as incorrect insights or inaccurate predictions, by removing errors and redundancies. When data is meticulously validated and free from inconsistencies, AI models can perform without the setbacks caused by “noisy” or flawed data. This ensures AI algorithms work with precise inputs, producing trustworthy results that bolster strategic decision-making.

Structure Format

While AI systems can process unstructured data (e.g., text, images, videos), structured data vastly improves processing speed and accuracy. Organized in databases or tables, structured data is easier to search, query, and analyze, significantly reducing the computational burden on AI systems. With AI-ready data in structured form, models can perform complex operations and deliver insights faster, supporting agile and efficient AI applications. For instance, structured financial or operational data enables rapid trend analysis, fueling responsive decision-making processes.

Comprehensive Coverage

AI-ready data must cover a complete and diverse spectrum of relevant variables. This diversity helps AI algorithms account for different scenarios and real-world complexities, enhancing the model’s ability to make accurate predictions. 

For example, an AI model predicting weather patterns would benefit from comprehensive data, including temperature, humidity, wind speed, and historical patterns. With such diversity, the AI model can better understand patterns, make reliable predictions, and adapt to new situations, boosting overall decision quality.

Timeline and Relevance

For data to maintain its AI readiness, it must be current and pertinent to the task. Outdated information can lead AI models to make erroneous predictions or irrelevant decisions, especially in dynamic fields like finance or public health. AI-ready data integrates recent updates and aligns closely with the model’s goals, ensuring that insights are grounded in present-day realities. For instance, AI systems for fraud detection rely on the latest data patterns to identify suspicious activities effectively, leveraging timely insights to stay a step ahead of evolving threats.

Data Integrity and Security

Security and integrity are foundational to trustworthy AI-ready data. Data must remain intact and safe from breaches to preserve its authenticity and reliability. With robust data integrity measures—like encryption, access controls, and validation protocols—AI-ready data can be protected from unauthorized alterations or leaks. This security not only preserves the quality of the AI model but also safeguards sensitive information, ensuring compliance with privacy standards. In healthcare, for instance, AI models analyzing patient data require stringent security to protect patient privacy and trust.

Key Drivers of AI-Ready Data

Understanding the drivers behind the demand for AI-ready data is essential. Organizations can harness the power of AI technologies better by focusing on these factors.

Vendor-Provided Models

Many AI models, especially in generative AI, come from external vendors. To fully unlock their potential, businesses must optimize their data. Pre-trained models thrive on high-quality, structured data. By aligning their data with these models’ requirements, organizations can maximize results and streamline AI integration. This compatibility ensures that AI-ready data empowers enterprises to achieve impactful outcomes, leveraging vendor expertise effectively.

Data Availability and Quality

Quality data is indispensable for effective AI performance. Many companies overlook data challenges unique to AI, such as bias and inconsistency. To succeed, organizations must ensure that AI-ready data is accurate, representative, and free of bias. Addressing these factors establishes a strong foundation, enabling reliable, trustworthy AI models that perform predictably across use cases.

Disruption of Traditional Data Management

AI’s rapid evolution disrupts conventional data management practices, pushing for dynamic, innovative solutions. Advanced strategies like data fabrics and augmented data management are becoming critical for optimizing AI-ready data. Techniques like knowledge graphs enhance data context, integration, and retrieval, making AI models smarter. This shift reflects a growing need for data management innovations that fuel efficient, AI-driven insights.

Bias and Hallucination Mitigation

New solutions tackle AI-specific challenges, such as bias and hallucination. Effective data management structures and prepares AI-ready data to minimize these issues. By implementing strong data governance and quality control, companies can reduce model inaccuracies and biases. This proactive approach fosters more reliable AI models, ensuring that decisions remain unbiased and data-driven.

Integration of Structured and Unstructured Data

Generative AI blurs the line between structured and unstructured data. Managing diverse data formats is crucial for leveraging generative AI’s potential. Organizations need strategies to handle and merge various data types, from text to video. Effective integration enables AI-ready data to support complex AI functionalities, unlocking powerful insights across multiple formats.

5 Steps to AI-Ready Data

The ideal starting point for public-sector agencies to advance in AI is to establish a mission-focused data strategy. By directing resources to feasible, high-impact use cases, agencies can streamline their focus to fewer datasets. This targeted approach allows them to prioritize impact over perfection, accelerating AI efforts.

While identifying these use cases, agencies should verify the availability of essential data sources. Building familiarity with these sources over time fosters expertise. Proper planning can also support bundling related use cases, maximizing resource efficiency by reducing the time needed to implement use cases. Concentrating efforts on mission-driven, high-impact use cases strengthens AI initiatives, with early wins promoting agency-wide support for further AI advancements.

Following these steps can ensure agencies select the right datasets that meet AI-ready data standards.

Step 1: Build a Use Case Specific Data  Catalog

The chief data officer, chief information officer, or data domain owner should identify relevant datasets for prioritized use cases. Collaborating with business leaders, they can pinpoint dataset locations, owners, and access protocols. Tailoring data discovery to agency-specific systems and architectures is essential. Successful data catalog projects often include collaboration with system users and technical experts and leverage automated tools for efficient data discovery.

For instance, one federal agency conducted a digital assessment to identify datasets that drive operational efficiency and cost savings. This process enabled them to build a catalog accessible to data practitioners across the agency.

Step 2: Assess Data Quality and Completeness

AI success depends on high-quality, complete data for prioritized use cases. Agencies should thoroughly audit these sources to confirm their AI-ready data status. One national customs agency did this by selecting priority use cases and auditing related datasets. In the initial phases, they required less than 10% of their available data.

Agencies can adapt AI projects to maximize impact with existing data, refining approaches over time. For instance, a state-level agency improved performance by 1.5 to 1.8 times using available data and predictive analytics. These initial successes paved the way for data-sharing agreements, focusing investment on high-impact data sources.

Step 3: Aggregate Prioritized Data Sources

Selected datasets should be consolidated within a data lake, either existing or purpose-built on a new cloud-based platform. This lake serves analytics staff, business teams, clients, and contractors. For example, one civil engineering organization centralized procurement data from 23 resource planning systems onto a single cloud instance, granting relevant stakeholders streamlined access.

Step 4: Evaluate Data Fit

Agencies must evaluate AI-ready data for each use case based on data quantity, quality, and applicability. Fit-for-purpose data varies depending on specific use case requirements. Highly aggregated data, for example, may lack the granularity needed for individual-level insights but may still support community-level predictions. 

Analytics teams can enhance fit by:

Selecting data relevant to use cases.

Developing a reusable data model with the necessary fields and tables.

Systematically assessing data quality to identify gaps.

Enriching the data model iteratively, adding parameters or incorporating third-party data.

A state agency, aiming to support care decisions for vulnerable populations, found their initial datasets incomplete and in poor formats. They improved quality through targeted investments, transforming the data for better model outputs.

Step 5: Governance and Execution

Establishing a governance framework is essential to secure AI-ready data and ensure quality, security, and metadata compliance. This framework doesn’t require exhaustive rules but should include data stewardship, quality standards, and access protocols across environments.

In many cases, existing data storage systems can meet basic security requirements. Agencies should assess additional security needs, adopting control standards such as those from the National Institute of Standards and Technology. For instance, one government agency facing complex security needs for over 150 datasets implemented a strategic data security framework. They simplified the architecture with a use case–level security roadmap and are now executing a long-term plan.

For public-sector success, governance and agile methods like DevOps should be core to AI initiatives. Moving away from traditional development models is crucial, as risk-averse cultures and longstanding policies can slow progress. However, this transition is vital to AI-ready data initiatives, enabling real-time improvements and driving impactful outcomes.

Challenges to AI-Ready Data

While AI-ready data promises transformative potential, achieving it poses significant challenges. Organizations must recognize and tackle these obstacles to build a strong, reliable data foundation.

Data Silos

Data silos arise when departments store data separately, creating isolated information pockets. This fragmentation hinders the accessibility, analysis, and usability essential for AI-ready data.

Impact: AI models thrive on a comprehensive data view to identify patterns and make predictions. Silos restrict data scope, resulting in biased models and unreliable outputs.

Solution: Build a centralized data repository, such as a data lake, to aggregate data from diverse sources. Implement cross-functional data integration to dismantle silos, ensuring AI-ready data flows seamlessly across the organization.

Data Inconsistency

Variations in data formats, terms, and values across sources disrupt AI processing, creating confusion and inefficiencies.

Impact: Inconsistent data introduces errors and biases, compromising AI reliability. For example, a model with inconsistent gender markers like “M” and “Male” may yield flawed insights.

Solution: Establish standardized data formats and definitions. Employ data quality checks and validation protocols to catch inconsistencies. Utilize governance frameworks to uphold consistency across the AI-ready data ecosystem.

Data Quality

Poor data quality—like missing values or errors—undermines the accuracy and reliability of AI models.

Impact: Unreliable data leads to skewed predictions and biased models. For instance, missing income data weakens a model predicting purchasing patterns, impacting its effectiveness.

Solution: Use data cleaning and preprocessing to resolve quality issues. Apply imputation techniques for missing values and data enrichment to fill gaps, reinforcing AI-ready data integrity.

Data Privacy and Security

Ensuring data privacy and security is crucial, especially when managing sensitive information under strict regulations.

Impact: Breaches and privacy lapses damage reputations and erodes trust, while legal penalties strain resources. AI-ready data demands rigorous security to safeguard sensitive information.

Solution: Implement encryption, access controls, and data masking to secure AI-ready data. Adopt privacy-enhancing practices, such as differential privacy and federated learning, for safer model training.

You can read about the pillars of AI security.

Skill Shortages

Developing and maintaining an AI-ready data infrastructure requires specialized skills in data science, engineering, and AI.

Impact: Without skilled professionals, organizations struggle to govern data, manage quality, and design robust AI solutions, stalling progress toward AI readiness.

Solution: Invest in hiring and training for data science and engineering roles. Collaborate with external consultants or partner with AI and data management experts to bridge skill gaps.

Why is AI-Ready Data Important?

Accelerated AI Development

AI-ready data minimizes the time data scientists spend on data cleaning and preparation, shifting their focus to building and optimizing models. Traditional data preparation can be tedious and time-consuming, especially when data is unstructured or lacks consistency. With AI-ready data, data is pre-cleaned, labeled, and structured, allowing data scientists to jump straight into analysis. This efficiency translates into a quicker time-to-market, helping organizations keep pace in a rapidly evolving AI landscape where every minute counts.

Improved Model Accuracy

The accuracy of AI models hinges on the quality of the data they consume. AI-ready data is not just clean; it’s relevant, complete, and up-to-date. This enhances model precision, as high-quality data reduces biases and errors. For instance, if a retail company has AI-ready data on customer preferences, its models will generate more accurate recommendations, leading to higher customer satisfaction and loyalty. In essence, AI-ready data helps unlock better predictive accuracy, ensuring that organizations make smarter, data-driven decisions.

Streamlined MLOps for Consistent Performance

Machine Learning Operations (MLOps) ensure that AI models perform consistently from development to deployment. AI-ready data plays a vital role here by ensuring that both historical data (used for training) and real-time data (used in production) are aligned and in sync. This consistency supports smoother transitions between training and deployment phases, reducing model degradation over time. Streamlined MLOps mean fewer interruptions in production environments, helping organizations implement AI faster, and ensuring that models remain robust and reliable in the long term.

Cost Reduction Through Optimized Data Protection

AI projects can be costly, especially when data preparation takes a significant portion of a project’s budget. AI-ready data cuts down the need for extensive manual preparation, enabling engineers to invest time in high-value tasks. This shift not only reduces labor costs but also shortens project timelines, which is particularly advantageous in competitive industries where time-to-market can impact profitability. In essence, the more AI-ready a dataset, the less costly the AI project becomes, allowing for more scalable AI implementations.

Improved Data Governance and Compliance

In a regulatory environment, data governance is paramount, especially as AI decisions become more scrutinized. AI-ready data comes embedded with metadata and lineage information, ensuring that data’s origin, transformations, and usage are documented. This audit trail is crucial when explaining AI-driven decisions to stakeholders, including customers and regulators. Proper governance and transparency are not just compliance necessities—they build trust and enhance accountability, positioning the organization as a responsible AI user.

Future-Proofing for GenAI

With the rapid advancement in generative AI (GenAI), organizations need to prepare now to capitalize on future AI applications. Forward-thinking companies are already developing GenAI-ready data capabilities, setting the groundwork for rapid adoption of new AI technologies.

AI-ready data ensures that, as the AI landscape evolves, the organization’s data is compatible with new AI models, reducing rework and accelerating adoption timelines. This preparation creates a foundation for scalability and adaptability, enabling companies to lead rather than follow in ‌AI evolution.

Reducing Data Preparation Time for Data Scientists

It’s estimated that data scientists spend around 39% of their time preparing data, a staggering amount given their specialized skill sets. By investing in AI-ready data, companies can drastically reduce this figure, allowing data scientists to dedicate more energy to model building and optimization. When data is already clean, organized, and ready to use, data scientists can direct their expertise toward advancing AI’s strategic goals, accelerating innovation, and increasing overall productivity.

Conclusion

In the data-driven landscape, preparing AI-ready data is essential for any organization aiming to leverage artificial intelligence effectively. AI-ready data is not just about volume; it’s about curating data that is accurate, well-structured, secure, and highly relevant to specific business objectives. High-quality data enhances the predictive accuracy of AI models, ensuring reliable insights that inform strategic decisions. By investing in robust data preparation processes, organizations can overcome common AI challenges like biases, errors, and data silos, which often lead to failed AI projects.

Moreover, AI-ready data minimizes the time data scientists spend on tedious data preparation, enabling them to focus on building and refining models that drive innovation. For businesses, this means faster time-to-market, reduced operational costs, and improved adaptability to market changes. Effective data governance and security measures embedded within AI-ready data also foster trust, allowing organizations to meet regulatory standards and protect sensitive information. 

As AI technology continues to advance, having a foundation of AI-ready data is crucial for scalability and flexibility. This preparation not only ensures that current AI applications perform optimally but also positions the organization to quickly adopt emerging AI innovations, such as generative AI, without extensive rework. In short, prioritizing AI-ready data today builds resilience and agility, paving the way for sustained growth and a competitive edge in the future.

Source URL: https://www.techaheadcorp.com/blog/what-is-ai-ready-data-how-to-get-your-there/

[miskinmusic23-24]

You will have noticed that the last part of your Project Proposal is titled ‘Proposed Research Sources & Bibliography (Harvard Format)’

In this section I need you to list the types of research you have already been using as well as those you anticipate using during the project.

Also I would like you to demonstrate here that you know how to use the Harvard system and then use it for every piece of research that you put onto your WIX site from now on

Why do we need to do this?

There are many reasons but the main two are:

Firstly it will help you to avoid accusations of plagiarism. So that you can include other peoples work on your site and be clear about what opinions are your own.

Secondly as we use so much research these days from the Internet from sites like Youtube, we need to show when we accessed the information because the person in control of the content could change it at any time.

When you have finished writing the other sections of your proposal then Post the first piece of secondary research from your research tab and include the Harvard Reference below it.

Below this post is an example from my own Youtube channel

Above is a link to a website called Neil’s toolbox, that will build your references for you. If you were referencing a Youtube video for example, you click on ‘referencing a website’ and simply fill in the information in the boxes below.

Author will be who’s channel it is

Article Title will be the name of the video

Name of Website will be Youtube

[katescomsformakers]

Week Four: Referencing/Citations

Book: Aciman, André. Call Me by Your Name. 2007.

Academic Journal: Berger, Patricia. Archives of Asian Art. 1966. Duke University Press, 2018, https://www.jstor.org/journal/archasiaart.

Blog: ‘Tofu - Pixel Art’. Tumblr, https://tofupixel.tumblr.com/. Accessed 21 Mar. 2024.

TV Episode: The Office. Directed by Randall Einhorn, Ep 1, 2005.

Podcast: Goalhanger Podcasts. The Rest Is History. 432.

Instagram Post: Jenner, Kylie. @kyliejenner, 14 Mar. 2024, https://www.instagram.com/p/C4Q2EDOp0rN/.

To find my resources, I used mostly Google as it is what I'm familiar with, however in the future I will use Discover and Google Scholar as they have more resources that a regular google search doesn't get you. To find an academic journal as I didn't know any off the top of my head, I used a website; JSTOR Home. https://www.jstor.org/. Accessed 21 Mar. 2024. It has an extensive database and is a resource I will use in future assignments. As per recommendation on Stream, I downloaded Zotero as an easy way to generate citations. I found I had to manually entry all of the relevant information as pasting a URL didn't give as accurate of a reference. I filled in about 4-7 relevant information boxes to generate what I needed. ZoteroBib: Fast, Free Bibliography Generator - MLA, APA, Chicago, Harvard Citations. https://zbib.org/. Accessed 21 Mar. 2024. It was interesting to note that MLA formats change with every form of content; rearranging the order of author, title, etc and also what parts are italicised and what isn't. Massey OWLL was also a helpful resource during this. MLA Interactive - OWLL - Massey University. https://owll.massey.ac.nz/referencing/mla-interactive.php. Accessed 21 Mar. 2024.