Living in a Minority Food Culture: A Phenomenological Investigation of Being Vegetarian/Vegan
Bibliographic record
Abstract
This phenomenological investigation aims to explore the lived experience of being vegan or vegetarian in a society and culture that is primarily non-vegetarian. As members of a unique minority group, vegans and vegetarians can sometimes be misunderstood by non-vegetarians and stereotyped as judgmental or difficult to deal with. Living with this type of misunderstanding from others can lead to feelings such as worry, loneliness, and fear. As such, the use of phenomenological inquiry is well suited to uncover the lived experience this phenomenon in such a way that no other method of inquiry could. The author brings forward themes that emerged from in depth conversations with two vegan/vegetarian participants, and draws from her own personal experiences as a vegetarian to supplement the data and further uncover the phenomenon. Themes are brought forward through the use of, among other works, Hyppolite’s (1956) and Bachelard’s (1994) descriptions of “inside vs. outside” and van Manen and Levering’s (1996) notion of secrecy.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".