Bibliographic record
Abstract
Can a feminist, justice-oriented approach to environmental care function through the concept of the Anthropocene? This article argues that by foregrounding girlhood and young women's experiences, an ecofeminist approach to environmental education benefits the outdoor education field and environmentalist action alike. The argument is based on ethnographic research from 2018 at Cottonwood Gulch—an outdoor education program based in New Mexico, USA. It focuses on an all-girls group and the relationships they created with wildlife and wild spaces throughout their time in the outdoors immersion program. The article explores how an ecofeminist approach to the girls' education strengthened their responsible relationships with environments. Cottonwood Gulch created a sense of home in the landscapes it explored, and it encouraged intimacy between participants and between participants and wildlife. Through this approach the girls came to know "land as home" and to understand caretaking as central to ecological responsibility and environmentalism. The article explores the entanglement of environmentalism and feminism discussed through ecofeminist approaches and problematizes the Anthropocene through this lens. It asks us to look beyond the concept of the Anthropocene and instead take up understanding of the Capitalocene, allowing ecofeminist thought and work to inspire a justice-oriented approach to environmentalism and environmental education.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".