Uncommon grounds : LGBTIQ farmers, agriculture, and ecologies of social difference
Bibliographic record
Abstract
This work is an ethnography of queer farmers throughout British Columbia and acknowledges that by working within such a diverse population, there exists no singular representation of “queer individuals,” “farmers,” and / or “queer farmers.” The research design integrates a qualitative, post-structuralist ethnographic and auto-ethnographic methodology based upon individual narratives and a review of both local (British Columbia) and non-local (national and international) print and web sources (academic and non-academic) related to gender, and especially sexuality, in agricultural production and practice. This study recognizes the existence of ecologies of social difference. I define ecologies of social difference as the role of ecological indicators, settings, and contexts as mediators and moderators in the intersections of social difference (i.e., the role of ecology in shaping both positively and negatively greater inequalities, inequities, injustices). This study draws from several intellectual lineages, from queer theory to feminist political ecology, to illustrate how agriculture might be transformed within a queer ecological context. Rooted in my belief that understandings of agriculture and ecology are shaped and impacted by gender and sexuality even as understandings of gender and sexuality are shaped and impacted by practices within and perceptions of agriculture and ecology, this work seeks to challenge heteronormative assumptions of both gender and sexuality and agriculture and ecology. It presupposes that queer sexualities can provide lenses through which farmers are not only creating new agricultural practices, but also new queer identities. These new, heretofore unstudied, lenses may then lead to the identification of new perspectives, practices, innovations and understandings of agricultural and ecological sustainability.
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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 | 0.002 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".