Bibliographic record
Abstract
The canvas tote bag, often branded with the name and logo of a popular cultural institution or bookstore, has become a shorthand for an individual’s accumulated cultural capital; this seemingly innocuous accessory has the power to signal to one’s peers the level of their engagement with the cultural and creative industries in a seemingly casual but deeply coded manner. The literary festival presents the perfect opportunity for individuals to signal to those around them that they, for example, subscribe to the New Yorker or donate money to the V&A museum. This article presents the findings of an observational study conducted at four literary festivals in Australia, the United Kingdom and the United States. Four distinct categories emerged from this analysis of tote bags carried at literary festivals: the festival tote that is sold at the festival; totes associated with cultural institutions; totes with political, satirical or ironic slogans; totes that are not associated with any particular arts or cultural brand or institution. I argue that, especially where the first three categories are concerned, the tote bags carried at literary festivals are consciously chosen for the purpose of signalling one’s cultural capital.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".