EthnoGRAPHIC: An Interview
Bibliographic record
Abstract
The interview focuses on the book series EthnoGRAPHIC (University of Toronto Press) and the graphic novel Lissa. A Story about Medical Promise, Friendship and Revolution, the first book of the series. Four points arise from the interview with authors Sherine Hamdy and Coleman Nye, and with the filmmaker Francesco Dragone, who documented their research process. First, the problem of funding multimedia and innovative research projects, aimed to find new ways of communicating social research. Second, the question to what extent such projects are recognized and legitimated within the Academia. Third, the audience potentially interested in reading (ethno)graphic novels and, relatedly, their usability in teaching social sciences. Finally, the concerns and practicalities in putting together different narrative forms. This effort of combining several ways of representing social reality, also concerns the organization of the research itself as well as conducting fieldwork and the capability of thinking “graphically” from scratch instead of adapting textual data collected during the research.
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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".