A scoping review of the integration of empowerment-based perspectives in quantitative intersectional stigma research
Bibliographic record
Abstract
The genesis of the concept of intersectionality was a call to dismantle interlocking systems of oppression - racial, sexual, heterosexual, and class-based - in order to realise liberation of Black women and other women of colour. Intersectionality holds the radical potential to amplify collective efficacy, community solidarity, and liberation. The extension of intersectionality into stigma research has resulted in an increased focus on intersectional stigma in quantitative research. This raises questions regarding how the radical and liberatory potential of intersectionality is applied in stigma research. Specifically, empowerment-based perspectives may be overlooked in quantitative intersectional stigma research. We conducted a scoping review to document if and how empowerment-based perspectives were included in intersectional stigma quantitative studies. We identified and included 32 studies in this review that examined varied stigmas, most commonly related to race, gender, HIV and sexual orientation. In total 13/32 (40.6%) of these studies reported on empowerment-based factors; most of these examined social support and/or resilience. Taken together, findings suggest that the quantitative intersectional stigma research field would benefit from expansion of concepts studied to include activism and solidarity, as well as methodological approaches to identify the protective roles of empowerment-based factors to inform health and social justice-related programmes and policy.
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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 | 0.033 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.032 | 0.034 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".