Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Through content analysis of three relevant research essays, this study examines how vegan communities contribute to the reformation of the cultural identity of vegan-identifying persons. Jessica Greenebaum’s (2012) research on identity and authenticity studies the different ways in which people classify themselves, and how they negotiate and reform their cultural identities. Elizabeth Cherry’s (2006) research on veganism as a cultural movement emphasizes the importance that a strong social network has on maintaining a vegan lifestyle. Finally, Mary Jane Collier’s (2015) article on identity and communication identifies norms, symbols, and meanings unique to the vegan culture and community. I hypothesize that ethical concerns are the main force behind adopting a vegan lifestyle. I want to further understand the role that community plays in forming a vegan identity, and, overall, to affirm that community is essential to maintaining, and thriving in, a vegan lifestyle. Vegan individuals, who are able to connect with other vegans, adhere more strictly to a plant-based diet. In comparison, vegans who do not partake in any social organizations or vegan networks are more likely to adapt the definition of veganism to fit their lifestyle. Community and networks play a considerable role in accountability, and they allow people not only to define themselves as vegan, but also permit others to identify as vegan, too.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it