Bibliographic record
Abstract
This article provides an ethnographic analysis of the agency of women who reside in the rural areas of the Argentine Pampas, based on their promotion and production of agroecological family horticulture. The recognition of these women’s agency through care – care of their children, global care, and green care – offers a significant challenge to some metrocentric and Eurocentric feminist perspectives that claim care work can only be oppressive for women. The first of these types of care empowers women to improve the nutrition of their children. It also relates to another underlying type of care, which is to provide a sufficiently robust education as to ensure their children have a better and alternative future. The second type of care has the power to socially transform the territorial space of the district’s countryside and its marginalized populations which, through care, acquire greater public and political attention. The third type of care empowers women to transform and care for the environment, and is exercised by not using pesticides in horticultural production and by disseminating knowledge on the matter. In line with discussions of postcolonial feminism (Abu-Lughod, 1986; Mahmood, 2001; Suárez Navaz, 2008), I argue that certain properties that are attributed to women relative to caregiving – by way of a dichotomous view of gender relations – fuel their agency: for these women the cultivation of vegetables is a form of agency that actively combats food, training and labor inequality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".