Reading Group as Method for Feminist Environmental Humanities
Bibliographic record
Abstract
This article argues that reading groups are a collective field building and research method in Feminist Environmental Humanities, an interdisciplinary scholarly area at the intersections of feminist social justice and environmental concerns.We begin by historicising three Australian Feminist Environmental reading groups (COMPOSTING Feminisms, Eco Feminist Fridays, The Ediths) within a longer feminist tradition, then demonstrate how they respond to declining research funding in the neoliberal university and accelerating ecological crisis.Drawing on survey data, we first thematically code and analyse the results to categorise the groups' functions and impacts.Departing from more traditional data analysis, we then develop a method of interpretation called 'transversal poetics'.Via a captioned photo essay, we unpack how transversal poetics yields new ways of reading the data.We show how this practice-led, creative method reveals additional themes and crystallises the reading groups' key ethos: building situated communities of care across difference.Overall, the research underscored that while never free of ethical tensions and compromises, Feminist Environmental reading groups can be a playful, affirmative and generative method for field building and research.
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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 | 0.055 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".