#so long as you do not inherently ascribe certain traits as being indicative of who somebody Is

[uncanny-tranny]

You know, I feel like other trans people might get this, but it's honestly kind of refreshing when a cis person has, like, undeniable tboy/tgirl/whatever swag. It's like when you come across somebody who speaks the same language as you and you only find out when they start speaking it, too.

[yunis-speaks]

The Conversation Surrounding Narcissism and "Narcissistic Abuse"

I think the first question to ask ourselves here would be "what is narcissistic abuse?" What constitutes that specific type of abuse? In which the answer we usually get is: controlling behaviour, uneven power dynamics, blame shifting, guilting, gaslighting, rejection and degradation and occasionally some aspects of physical abuse. This is where we go, "but are those exclusive to 'narcissistic abuse'?" In which the answer is a simple no. So let's unpack that, why do we use the term "narcissistic abuse"? What does it imply?

The usage of the term narcissistic abuse has many reasons, but one of the most prominent and prevalent ones is 'othering'. If abuse is inherent to narcissists, then we can't possibly be abusers — and any 'toxic' traits we may have in regards to how we deal with relationships (say, being overly dismissive) can be ignored, because we're not narcissists and therefore not abusers and cannot hold what we label "narcissistic traits" that would be indicative to abuse.

Another is that by othering the narcissist, we can have specific 'traits' that can indicate that a person is a narcissist, and therefore an abuser, in which you now clearly identify the 'hidden evil person' in the crowd. Based on which, you can avoid the narcissist and any subsequent abuse. Here, we find some problematic implications that having gone through abuse is the victim's fault for failing to notice the 'evil scheming narcissist" first.

When narcissism is successfully alienated and othered, then intrinsically tied to abuse, abusers get described as narcissists and armchair-diagnosed with narcissism. Where certain victims of abuse will claim that their abuse is unique and special, and that the only people who could understand them is people who went through the same unique and special abuse (because their abusers were unique and special).

Ultimately, this serves to demonise narcissists and narcissism. There is nothing that is 'unique' or exclusive to "narcissistic abuse" which justifies the existence of the term beyond ableism. The traits ascribed to narcissistic abuse are simply what constitutes emotional abuse, and in much more rare cases complex/sophisticated abuse.

The term "narcissistic abuse" as such only ever dehumanises and demonises narcissists. It does not allowing them their humanity or complex experiences, instead shoving them into boxes where their existence is equated to abuse, and their disorder to being an abuser.

It only further stigmatises an already heavily stigmatised disorder, and cuts them off from societal, social, and professional support.

Narcissists are "abusers", "lost causes", they "cannot be treated". They are not human. They are sub-human. They are "sadistic" and "cruel" and "do not care for others." If all a narcissist does is bring suffering and 'be evil' — the world is better off without narcissists.

This is what a narcissist has to deal with day-to-day. From friends, family, mental health professionals. That they are lost causes and cannot be treated, that they are deep-down, inherently evil. Nevermind that all these opinions are informed by stereotypes and the stigma surrounding narcissism, and that none of that is true.

Nevermind the fact that narcissistic personality disorder forms as a result of abuse and associated trauma (in Ireland, it was once contemplated to change the categorical name from 'personality disorder' to 'complex trauma responses') or that narcissists are more suspectable to abuse.

Narcissism doesn't make an abuser. Abuse makes an abuser.

Then comes the question, "but wouldn't being a narcissist influence the abuse?" The short answer is yes. The long one is that mental illness influences how you perceive and interact with the world, it influences all things including 'abuse' were the mentally ill person an abuser. However, it does not make them an abuser. If a depressed parent abused their child, say as influenced by their depression, with no energy and little to no motivation to care for their child and high irritability should they ask for that care or any energy-inducing things (so in here, through neglect) we wouldn't call it "depressive abuse" or say they abused the child because they're depressed in a 1:1 connection between depression and abuse where all depressed people are abusive or 'more likely' to be abusive.

That simply wouldn't be true, and not to mention extremely ableist. And yet, we do that exact same thing with narcissism to alarming degrees where the word "narcissist" has become synonymous with "abuser".

[sawyerlex]

The Data That Turned the World Upside Down

Full Story Here

Motherboard

Hannes Grassegger and Mikael Krogerus Jan 28 2017, 9:15am

Anyone who has not spent the last five years living on another planet will be familiar with the term Big Data. Big Data means, in essence, that everything we do, both on and offline, leaves digital traces. Every purchase we make with our cards, every search we type into Google, every movement we make when our mobile phone is in our pocket, every "like" is stored. Especially every "like." For a long time, it was not entirely clear what use this data could have—except, perhaps, that we might find ads for high blood pressure remedies just after we've Googled "reduce blood pressure."

On November 9 and the results of the election certain, it became clear that maybe much more is possible. The company behind Trump's online campaign—the same company that had worked for Leave.EU in the very early stages of its "Brexit" campaign—was a Big Data company: Cambridge Analytica.

To understand the outcome of the election—and how political communication might work in the future—we need to begin with a strange incident at Cambridge University in 2014, at Kosinski's Psychometrics Center.

Psychometrics, sometimes also called psychographics, focuses on measuring psychological traits, such as personality. In the 1980s, two teams of psychologists developed a model that sought to assess human beings based on five personality traits, known as the "Big Five." These are: openness (how open you are to new experiences?), conscientiousness (how much of a perfectionist are you?), extroversion (how sociable are you?), agreeableness (how considerate and cooperative you are?) and neuroticism (are you easily upset?). Based on these dimensions—they are also known as OCEAN, an acronym for openness, conscientiousness, extroversion, agreeableness, neuroticism—we can make a relatively accurate assessment of the kind of person in front of us. This includes their needs and fears, and how they are likely to behave. The "Big Five" has become the standard technique of psychometrics. But for a long time, the problem with this approach was data collection, because it involved filling out a complicated, highly personal questionnaire. Then came the Internet. And Facebook. And Kosinski.

In 2012, Kosinski proved that on the basis of an average of 68 Facebook "likes" by a user, it was possible to predict their skin color (with 95 percent accuracy), their sexual orientation (88 percent accuracy), and their affiliation to the Democratic or Republican party (85 percent). But it didn't stop there. Intelligence, religious affiliation, as well as alcohol, cigarette and drug use, could all be determined. From the data it was even possible to deduce whether someone's parents were divorced.

Above, Michal Kosinski

The strength of their modeling was illustrated by how well it could predict a subject's answers. Kosinski continued to work on the models incessantly: before long, he was able to evaluate a person better than the average work colleague, merely on the basis of ten Facebook "likes." Seventy "likes" were enough to outdo what a person's friends knew, 150 what their parents knew, and 300 "likes" what their partner knew. More "likes" could even surpass what a person thought they knew about themselves. On the day that Kosinski published these findings, he received two phone calls. The threat of a lawsuit and a job offer. Both from Facebook.

But it was not just about "likes" or even Facebook: Kosinski and his team could now ascribe Big Five values based purely on how many profile pictures a person has on Facebook, or how many contacts they have (a good indicator of extraversion). But we also reveal something about ourselves even when we're not online. For example, the motion sensor on our phone reveals how quickly we move and how far we travel (this correlates with emotional instability). Our smartphone, Kosinski concluded, is a vast psychological questionnaire that we are constantly filling out, both consciously and unconsciously.

Above all, however—and this is key—it also works in reverse: not only can psychological profiles be created from your data, but your data can also be used the other way round to search for specific profiles: all anxious fathers, all angry introverts, for example—or maybe even all undecided Democrats? Essentially, what Kosinski had invented was sort of a people search engine. He started to recognize the potential—but also the inherent danger—of his work.

To him, the internet had always seemed like a gift from heaven. What he really wanted was to give something back, to share. Data can be copied, so why shouldn't everyone benefit from it? It was the spirit of a whole generation, the beginning of a new era that transcended the limitations of the physical world. But what would happen, wondered Kosinski, if someone abused his people search engine to manipulate people? He began to add warnings to most of his scientific work. His approach, he warned, "could pose a threat to an individual's well-being, freedom, or even life." But no one seemed to grasp what he meant.

Around this time, in early 2014, Kosinski was approached by a young assistant professor in the psychology department called Aleksandr Kogan. He said he was inquiring on behalf of a company that was interested in Kosinski's method, and wanted to access the MyPersonality database. Kogan wasn't at liberty to reveal for what purpose; he was bound to secrecy.

At first, Kosinski and his team considered this offer, as it would mean a great deal of money for the institute, but then he hesitated. Finally, Kosinski remembers, Kogan revealed the name of the company: SCL, or Strategic Communication Laboratories. Kosinski Googled the company: "[We are] the premier election management agency," says the company's website. SCL provides marketing based on psychological modeling. One of its core focuses: Influencing elections. Influencing elections? Perturbed, Kosinski clicked through the pages. What kind of company was this? And what were these people planning?

What Kosinski did not know at the time: SCL is the parent of a group of companies. Who exactly owns SCL and its diverse branches is unclear, thanks to a convoluted corporate structure.

On further investigation, he discovered that Aleksandr Kogan had secretly registered a company doing business with SCL. According to a December 2015 report in The Guardian and to internal company documents given to Das Magazin, it emerges that SCL learned about Kosinski's method from Kogan.

Kosinski came to suspect that Kogan's company might have reproduced the Facebook "Likes"-based Big Five measurement tool in order to sell it to this election-influencing firm.

Kosinski came to suspect that Kogan's company might have reproduced the Facebook "Likes"-based Big Five measurement tool in order to sell it to this election-influencing firm.

Above, Alexander Nix

All was quiet for about a year. Then, in November 2015, the more radical of the two Brexit campaigns, "Leave.EU," supported by Nigel Farage, announced that it had commissioned a Big Data company to support its online campaign: Cambridge Analytica. The company's core strength: innovative political marketing—microtargeting—by measuring people's personality from their digital footprints, based on the OCEAN model.

After Brexit, and the results achieved by Cambridge Analytica, Trump hires the firm to be his digital campaign company.  (Cambridge Analytica counts among its clients the U.S. State Department, and has been reported to have communicated with British Prime Minister Theresa May.  Steve Bannon is a board member.)  Up to this point, Trump's digital campaign had consisted of more or less one person: Brad Parscale, a marketing entrepreneur and failed start-up founder who created a rudimentary website for Trump for $1,500. The 70-year-old Trump is not digitally savvy—there isn't even a computer on his office desk. Trump doesn't do emails, his personal assistant once revealed. She herself talked him into having a smartphone, from which he now tweets incessantly.

Alexander Nix, chief executive officer of Cambridge Analytica, explains how it all works.  "At Cambridge," he said, "we were able to form a model to predict the personality of every single adult in the United States of America." According to Nix, the success of Cambridge Analytica's marketing is based on a combination of three elements: behavioral science using the OCEAN Model, Big Data analysis, and ad targeting. Ad targeting is personalized advertising, aligned as accurately as possible to the personality of an individual consumer.

Nix candidly explains how his company does this. First, Cambridge Analytica buys personal data from a range of different sources, like land registries, automotive data, shopping data, bonus cards, club memberships, what magazines you read, what churches you attend. Nix displays the logos of globally active data brokers like Acxiom and Experian—in the US, almost all personal data is for sale. For example, if you want to know where Jewish women live, you can simply buy this information, phone numbers included. Now Cambridge Analytica aggregates this data with the electoral rolls of the Republican party and online data and calculates a Big Five personality profile. Digital footprints suddenly become real people with fears, needs, interests, and residential addresses.

The methodology looks quite similar to the one that Michal Kosinski once developed. Cambridge Analytica also uses, Nix told us, "surveys on social media" and Facebook data. And the company does exactly what Kosinski warned of: "We have profiled the personality of every adult in the United States of America—220 million people," Nix boasts.

Trump's striking inconsistencies, his much-criticized fickleness, and the resulting array of contradictory messages, suddenly turned out to be his great asset: a different message for every voter. The notion that Trump acted like a perfectly opportunistic algorithm following audience reactions is something the mathematician Cathy O'Neil observed in August 2016.

"Pretty much every message that Trump put out was data-driven," Alexander Nix remembers. On the day of the third presidential debate between Trump and Clinton, Trump's team tested 175,000 different ad variations for his arguments, in order to find the right versions above all via Facebook. The messages differed for the most part only in microscopic details, in order to target the recipients in the optimal psychological way: different headings, colors, captions, with a photo or video. This fine-tuning reaches all the way down to the smallest groups, Nix explained in an interview with us. "We can address villages or apartment blocks in a targeted way. Even individuals."

In the Miami district of Little Haiti, for instance, Trump's campaign provided inhabitants with news about the failure of the Clinton Foundation following the earthquake in Haiti, in order to keep them from voting for Hillary Clinton. This was one of the goals: to keep potential Clinton voters (which include wavering left-wingers, African-Americans, and young women) away from the ballot box, to "suppress" their vote, as one senior campaign official told Bloomberg in the weeks before the election. These "dark posts"—sponsored news-feed-style ads in Facebook timelines that can only be seen by users with specific profiles—included videos aimed at African-Americans in which Hillary Clinton refers to black men as predators, for example.

 Just how precisely the American population was being targeted by Trump's digital troops at that moment was not visible, because they attacked less on mainstream TV and more with personalized messages on social media or digital TV. And while the Clinton team thought it was in the lead, based on demographic projections, Bloomberg journalist Sasha Issenberg was surprised to note on a visit to San Antonio—where Trump's digital campaign was based—that a "second headquarters" was being created. The embedded Cambridge Analytica team, apparently only a dozen people, received $100,000 from Trump in July, $250,000 in August, and $5 million in September. According to Nix, the company earned over $15 million overall. (The company is incorporated in the US, where laws regarding the release of personal data are more lax than in European Union countries. Whereas European privacy laws require a person to "opt in" to a release of data, those in the US permit data to be released unless a user "opts out.")

The measures were radical: From July 2016, Trump's canvassers were provided with an app with which they could identify the political views and personality types of the inhabitants of a house. It was the same app provider used by Brexit campaigners. Trump's people only rang at the doors of houses that the app rated as receptive to his messages. The canvassers came prepared with guidelines for conversations tailored to the personality type of the resident. In turn, the canvassers fed the reactions into the app, and the new data flowed back to the dashboards of the Trump campaign.

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