Bibliographic record
Abstract
Abstract As a conceptual and analytic framework, intersectionality has informed, and can transform, how scholars approach psychology and its history. Intersectionality provides a framework for examining how multiple social categories combine in systems characterized by both oppression and privilege to affect the experiences of those occupying the intersections of these social categories. The concept has its origins in the writings of Black feminists and critical race theorists in the 1970s and 1980s. Since that time, many critical debates about the definition, uses, and even misuses of intersectionality have been put forward by scholars in many fields. In psychology, the uptake of intersectionality as a methodological and epistemological framework has been undertaken largely by feminist psychologists. In this context, intersectionality has been used as both a logic for designing research, and as a perspective from which to critique the perpetuation of intersectional oppression latent in mainstream psychological research. In addition, intersectionality has also been applied to writing histories of psychology that attend to the operation of multiple intersecting forms of oppression and privilege. For example, historians of psychology have taken up intersectionality as a way to approach the intersections of scientific racism, sexism, and heterocentrism in the history of psychology’s concepts and theories. Intersectionality also has the potential for generating a more sophisticated historical understanding of social activism by psychologists. Finally, given that extant histories of psychology focusing on the American context have rendered the contributions of women of color largely invisible, intersectional analysis can serve to re-instantiate and foreground their experiences and contributions.
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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.015 | 0.136 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".