Liberating history: The context of the challenge of psychologists of color to American psychology.
Bibliographic record
Abstract
The history of race and ethnicity in North America is long and complex. It has been fraught with racism and various forms of oppression--intellectual, social, and physical--and defies easy analysis. This article examines the history of race and ethnicity in the United States, and how it played out in the field of psychology. Although other articles in this issue examine the specific impact of racism and internal colonialism on racial and ethnic minorities, this article places these events within an international context, specifically the post-World War II era when oppressed peoples around the world sought liberation from colonial oppressors. The article suggests that the struggles and successes of racial and ethnic minority psychologists may provide the best opportunity for American psychology to connect with emerging indigenous psychologies in other parts of the world, which represent the future of psychology in a globalizing world.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.050 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".