Bibliographic record
Abstract
This study explores the relationship between gender and veganism through a critical analysis of food-based discourse on three vegan blogs. As many researchers note, there is a strong association between meat and masculinity in North American society (Nath, 2011; Rothgerber, 2013; Rozin, Hormes, Faith & Wansink, 2012; Ruby & Heine, 2011; Sumpter, 2015). While some researchers argue that the practice of veganism inherently challenges traditional gender norms (Adams, 2015; Potts and Parry, 2010), in these blog posts there is little room for alternative gender performativity. Drawing upon critical feminist and vegan studies literature, and previous discourse analysis of food blogs, this research examines the intersections of gender and food through the practice of veganism. Furthermore, it analyses how the association between meat and masculinity is applied in the gendering of vegan food. I argue that the gendered discourse of vegan food on these blogs reinforces, rather than challenges, traditional gender norms through the use of tropes describing “carnivorous men” and “manly meals” with hopes of satiating male appetites.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".