Bibliographic record
Abstract
The increasing digitization of print media has resulted in the expansion of female genital mutilation (FGM) eradication efforts from print articles, editorials and novels, to online newspapers. The Guardian recently launched an online “End FGM Guardian Global Media Campaign,” incorporating video, film, and multimedia. This report reviews the digitization of FGM eradication efforts by comparing End FGM to past anti-female circumcision screen texts. Focusing on a film featured in the campaign, Shara Amin and Nabaz Ahmed’s 2007 documentary, A Handful of Ash, this report applies a post-colonial feminist critique of gender, sexuality and colonialism to examine how the digitization of pain and suffering is mobilized and consumed. Comparing the film to anti-circumcision screen texts, Ousmane Sembène’s Moolaadé and Sherry Hormann’s Desert Flower, this report historicizes the global media campaign and highlights its’ repackaging of past imperialist discourses on the body in new digitized ways.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".