Intersectionality as method for human rights research: Identifying who is made stateless and how through UN treaty body reviews
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
Few theories have generated the kind of international and interdisciplinary engagement as intersectionality. Nevertheless, intersectionality as a research paradigm has yet to gain ground in human rights research. People can experience the same rights violation on multiple grounds, yet human rights research design and methods—like rights frameworks and treaty bodies themselves—tend to examine each form of discrimination separately or additively. This article demonstrates the value of intersectionality as a methodological approach for human rights research by discussing feminist methodological insights developed through a global qualitative study of exclusionary birth registration practices that lead to statelessness. The discussion highlights three intersections that block access to birth certificates: gender, religious, and ethnic discrimination at the civil registrar; disability and ethnic discrimination in contexts of mobility; and discrimination based on gender, race, and migration status in reproductive healthcare. The conclusion offers human rights researchers an intersectional method for analyzing observations from all human rights mechanisms on a particular issue, to gain a more fulsome understanding of the operations of power that violate rights.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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