Bibliographic record
Abstract
The attempt to rearticulate traditional conceptions of nature can be both a useful strategy and a stumbling block when it comes to feminist examinations of the continuity between the objectification of women’s bodies and the domination of nature. This paper contributes to existing debates by providing a critique of what I term the “duality view” of nature: a view stipulating that nature is primarily characterised by a stable sexual duality, and advancing that the objectification of women’s bodies arises because the specificity of “femaleness” is ignored and duality is therefore neglected. I focus, specifically, on Alison Stone’s interpretation of Luce Irigaray, insofar as the account emerging from Stone’s interpretation clearly outlines the principles that most versions of the duality view should endorse. I problematise this account by showing that it becomes inconsistent with the critique of objectification which grounds it in the first place. I conclude by advancing that, overall, a view insisting on a natural sexual duality because of normative reasons conflicts with the feminist considerations at its basis. I also suggest that while the present analysis is primarily condemnatory, it can contribute to the development of feminist philosophies of nature by fleshing out avoidable pitfalls.
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 | 0.036 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.060 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".