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
Power-sharing may be a leading model for the inclusion of ethnic minorities in post-conflict government, but it is also considered a gender-blind approach to conflict regulation. In this article, I identify recent openings and shifts in power-sharing theory that suggest a new receptivity to the adoption of a gender perspective. Specifically, I focus on two major developments that have emerged over the last three decades – the widening of the power-sharing universe and the refinement of its institutional prescriptions – which have opened up analytical and political space for the inclusion of women in power-sharing theory. Building on these developments, I identify extant gender gaps in power-sharing theory, discuss strategies for overcoming them through the adoption of what I call least-ascriptive-most-prescriptive rules, and outline areas for future research on integrating a gender perspective into power-sharing theory and practice. While power-sharing theory may initially appear resistant to a gender intervention, I demonstrate there is new analytical space in the theory for such a venture.
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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it