The Suzanne Mackenzie Memorial Lecture: Rethinking the politics of feminist knowledge production in Anglo‐American geography
Bibliographic record
Abstract
It was Suzanne Mackenzie who first introduced me to the radical potential of a feminist mode of knowledge production in geography. In this paper, in Suzanne's honour, I ask how well feminist work in Anglo‐American geography is faring in terms of still generating new possibilities of knowledge and of existence. In asking this question I explore the work feminist interventions have done, and not done, in advancing possibilities within the discipline. I examine three aspects of feminist work in geography: looking back to (the collective forgetting of) feminist work prior to the 1960s; looking around at (the limitations of) feminist approaches to methodologies and methods; and looking ahead, in this current era characterized by anxiety and precarity, to (the as yet not undertaken) work on addressing these issues in the academy. I conclude by discussing the future of knowledge production in feminist geography.
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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 | 0.024 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.028 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.014 |
| 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".