Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores the historical context in which the concept of microaggression was produced and the psychological model that supported it. Microaggression has become a popular term used to describe the stress of minoritized groups beyond the experience of racism. This article presents a genealogical perspective informing the contemporary uses of the term. The concept of "microaggression" was developed by Black psychiatrist Chester Middlebrook Pierce (1927-2016), professor of psychiatry and education at Harvard University. Pierce played an important role in conceptualizing the relationships between the mental health of individuals and groups, and their environment. The career and story of Chester M. Pierce bear witness to the construction of the relation between racism and mental health in a therapeutic culture "in the making." Through a selective biographical account of the career and research of Pierce, this article examines what brought him to coin the term microaggression. It also considers the wider context of the political mobilization of behavioral sciences to understand and address social inequalities in the United States. The notion of microaggression was a conceptual tool used by Pierce to describe how racism is perpetuated as a psychological phenomenon and to help develop awareness of the need to propose defensive strategies. The contextualization of Pierce's research and achievements aims therefore to contribute to the history of American "therapeutic culture" and the discussion of the role that psychological concepts such as microaggression are assumed to play in the psychologization of power relations and everyday life. (PsycInfo Database Record (c) 2026 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it