Bibliographic record
Abstract
THE AMERICAN PSYCHOOGICAL ASSOCIATION (APA) welcomes the opportunity to provide comments on the Durban Review Outcome Document. APA is recognized with special consultative status at the United Nations and is accredited to the UN Department of Public Information as a non-governmental organization (NGO). APA’s representatives interact with the NGO community at the United Nations in New York, Geneva, and Vienna and APA serves on the CONGO Executive Committee. APA is the largest scientific and professional organization representing psychology in the United States and is the world’s largest association of psychologists. APA’s membership includes 150,000 researchers, educators, clinicians, consultants, and students. Through our 53 professional divisions of psychology and affiliations with 59 state, territorial, and Canadian provincial associations, APA works to advance psychology as a science, as a profession, and as a means of promoting health, education, and human welfare. APA was one of the many (NGOs) that sent a delegation to the World Conference Against Racism in 2001. The primary goal of APA’s interventions at that time, based on the APA Resolution on Racism and
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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.538 | 0.348 |
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".