The American Psychological Association and antisemitism: Toward equity, diversity, and inclusion.
Bibliographic record
Abstract
on Jul 15 2024 (see record 2025-04658-001). In the article, three sentences and a reference were redacted related to proceedings against a university concerning its psychology program because appropriate context was not provided in the article. All versions of this article have been corrected.] This article calls for the American Psychological Association (APA) to proactively include the elimination of antisemitism or prejudice against Jewish people in its current mission to disassemble all forms of racism from its organization as well as society. In this article, Jews (estimated as 2.4% of the population) are defined as a people with a common identity, ethnicity, and religion as they experience prejudice; their intersection in Jewish identity; the history and characteristics of antisemitism and its current manifestation in public life, academic institutions, and psychology. Despite Jews having made major contributions to the development of psychology as a profession, historically through the first half of the 20th century, Jews were systematically discriminated against within the discipline of psychology through quotas for acceptance into graduate training, discriminatory employment practices in university psychology departments, and most egregiously through the espousing of "scientific racism" including eugenics by prominent leaders in the APA. We describe how historically leaders in the APA engaged in overt and covert antisemitism while the APA continues to do little or nothing to combat it. We then offer suggestions for the mitigation and elimination of this form of bias, discrimination, and hate as it once again escalates in society. We recommend that the APA engages in research about antisemitism, its predictors, consequences, and power; evaluates the efficacy of intervention programs; encourages contact with various multicultural minoritized groups; and disseminates knowledge to educate about the psychological effects of antisemitism. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.077 | 0.027 |
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".