The racial economy of psychological care: Professionalism, social justice, and political action during american psychology’s communitarian moment.
Bibliographic record
Abstract
The 1960s and 1970s saw the overt "politicization" of the American Psychological Association as an organization. Politics in this context carried a dual meaning referring to both political lobbying to promote the interests of psychology as a health profession and grassroots political action to advance social justice causes. In the years between the passage of the Community Mental Health Act (1963) and the Vail Conference on levels and patterns of professional training in psychology (1973), these two forms of politics were intertwined. The first significant political mobilization of professional psychologists in the postwar era occurred over the staffing of community mental health centers in the mid-1960s. These creations of the Great Society social welfare programs provided a platform for pursuing bold experiments in structural interventions to improve the lives and mental health of minoritized Americans and came to serve as hubs for the Black psychology movement of the early 1970s. This alternative model for the profession received careful consideration at the Vail Conference. However, a different relationship between politics and the profession crystalized by 1980. The politics of professionalism in psychology took the form lobby on behalf of practitioners working independent practices to receive reimbursement from third-party health insurance providers. This shift in the political economy of mental health has obscured this earlier, communitarian moment in American psychology. The racial economy of psychology's professionalization was structural, but not inevitable. It resulted from a series of historical choices. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.005 | 0.003 |
| 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 | 0.041 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".