Bibliographic record
Abstract
Reshaping our methodological research tools for adequately capturing injustice and domination has been a central aspiration of feminist philosophy and social epistemology in recent years. There has been an increasingly empirical turn in recent feminist and political theorization, engaging with case studies and the challenges arising from conducting research in solidarity with unequal partners. I argue that these challenges cannot be resolved by merely adopting a norm and stance of deference to those in the struggle for justice. To conduct philosophical research in an engaged and solidaristic manner, I suggest that deference be supplemented by three methodological and normative principles: (1) epistemic humility, (2) accountability, and (3) coproducing knowledge. I situate these principles within contemporary philosophical work on solidarity and show how they might help confront power imbalances and other methodological hazards that arise when conducting research in solidarity with others. I arrive at these principles in part by critically reflecting on my own attempt to conduct research in solidarity with women’s rights activists in Senegal.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 teacher head, 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".