Bibliographic record
Abstract
The following article is built on an interview with two of the co-founders of The Fashion Studies Journal (FSJ), Lauren Downing Peters, Editor-in-Chief, and Laura Snelgrove, Editor-at Large. The interview was conducted and article was written by the editorial assistant at Fashion Studies, and is the first step towards creating a collaborative partnership between the two publications. FSJ began in 2012 as a traditional academic outlet and was relaunched in 2016 as an online journal, with a focus on taking a thoughtful approach to fashion from a range of perspectives while representing diverse voices. Meanwhile, in 2017 Fashion Studies launched as the first open-access journal in the transdisciplinary field of fashion studies, celebrating work that is focused on refashioning the world into a more equitable, just, and inclusive place. Connected through their similar journal names, the two publications soon realized that there were endless ways they could work together to further the field of fashion studies. In particular, the journals are united through their shared values of taking a critical approach to fashion, making fashion studies accessible, and building a fashion studies community. What follows are excerpts from the interview conducted between Fashion Studies and FSJ. Topics include how FSJ began, why the study of fashion is important, and advice for others hoping to establish themselves within the field.
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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".