Bibliographic record
Abstract
As Kay and Kenney-Lazar show, the concept of value holds appeal for political ecologists who seek to demystify and politicize the socio-ecological relations underpinning capitalist productions of nature. But there are challenges to using value to understand capitalist natures. Much of nature is not priced, and no nature labours for a wage. This makes the labour theory of value, which tends to be prominent even in discussions of a broadly defined value, difficult to apply to nature. Having wrangled with this ourselves, we turn (as Kay and Kenney-Lazar do) to feminist political economists, who have long theorized the unwaged realm within capitalist social relations. We find that these feminists, while not unconcerned with value, are instead often set on understanding how some work is persistently devalued, or denigrated, seen as worthless – which leads them to centre patriarchy in their analyses. Building from this, we suggest the need to centre anthropocentrism – to historicize and denaturalize devaluations of nature – within work on value and capitalist natures.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.096 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".