On being the target of prejudice: Educational implications
Bibliographic record
Abstract
Jews rule the world by proxy. Or so says the former prime minister of Malaysia, Dr. Mahathir Mohamad. In October 2003, in a speech to the 57-nation Islamic Summit in Malaysia, the then-prime minister lashed out at world Jewry. “The Europeans killed 6 million Jews out of 12 million,” stated Mohamad, “but today the Jews rule this world by proxy and get others to fight and die for them.” However disturbing and offensive Dr. Mohamad's words, they were not surprising to at least one of us who had spent a summer vacationing in Malaysia. Upon his arrival into Kuala Lumpur International Airport, Inzlicht noticed thousands of copies of The protocols of the learned elders of Zion on prominent display. Seeing this “classic” book – which is a fraudulent document purporting to describe a plan to achieve Jewish global domination – shocked and affronted Inzlicht, who happens to be Jewish. When he later entered the country, Inzlicht could not help but ask how his social identity was impacting the way others saw and interacted with him: He was mistrustful of others, watchful of what he said and did, and vigilant for the way others interacted with him. Having to enter a land that so vilifies and demonizes his Jewish identity was, in short, threatening. This chapter is concerned with the psychological effects of entering threatening environments, focusing not on the relatively clear case above, but on the more subtle and commonplace phenomenon of individuals entering environments where their cultural identity is devalued and stigmatized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".