Drawing-Writing-Up: En undersøgelse af udfordringer og potentialer ved etnografiske tegneserier
Bibliographic record
Abstract
Denne opgave undersøger de mulige potentialer og udfordringer ved etnografiske tegneserier i formidlingen af antropologisk viden. Dette undersøges gennem en analyse af to antropologiske tegneserie-projekter, henholdsvis Lissa: A Story about Medical Promise, Friendship and Re- volution (Hamdy & Nye 2017) og Gringo Love: Stories about Sex Tourism in Brazil (Carrier- Moisan 2020). Begge indgår i Toronto University Press’ ‘EthnoGRAPHIC’ serie, og er baseret på antropologers tidligere skrevne research, som herefter i et samarbejde med tegnere er omformet til tegneseriemediet. De to projekters tilgang til adaptation adskiller sig dog på måder, der rejser spørgsmål angående ‘sandhed’ og fiktion i antropologi. Derfor indsætter denne opgave drawing i writing-up, og undersøger valg og fravalg i adaptationen fra research til komposition af det færdige produkt. I opgaven argumenterer jeg for, at tegneseriers unikke måde at strukturere tid og rum kan give nye perspektiver på måden antropologisk viden formidles, ligesom jeg også opfordrer til en øget opmærksomhed på de områder, hvor mediet kan skabe udfordringer i en antropologisk kontekst.
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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 | 0.014 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.014 |
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".