Embodied and Emotional Knowledge of Oppression: Positive Contributions of a Relational Feminist Standpoint Theory
Bibliographic record
Abstract
This project is an exploration of how traditional epistemological methods have failed to or cannot make room for understanding the oppression of particular groups of people.My goals are explicitly feminist in that I aim to work to uncover these understandings so as to dismantle this oppression.With these goals in mind, I defend an epistemology that considers the importance of the social location of knowers.I turn to feminist standpoint This project would not have been possible without the strong support network of people I am so fortunate to have.I must first extend my most indebted gratitude to Christine Koggel, my thesis supervisor.Christine has had faith in this project since it was a mere spark of my varied philosophical and feminist interests, and has been integral to helping me hone it into the thesis it has become.I am so privileged to have had Christine's guidance, wisdom, and patience along this vast undertaking, which otherwise would not have been possible.I am in complete awe of your commitment to my success while also supervising another very demanding
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.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| 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".