Bibliographic record
Abstract
The issue 5 of antiAtlas Journal addresses questions of Air Deportation through 14 international articles and unpublished researches. It is based on the Air Deportation project led by the political sociologist William Walters (dir.) and the anthropologists Clara Lecadet and Cédric Parizot, and on contributions from a call for proposals. Its design is created by Thierry Fournier, artist and curator. This issue is supported by the Social Sciences and Humanities Research Council of Canada.Table of contentsWilliam Walters, Clara Lecadet and Cédric Parizot, Editorial and table of contents (EN)William Walters, Clara Lecadet and Cédric Parizot, Introduction: Air Deportation, (in)visibility, Power and Resistance (EN)Helen Brewer, How to stop a Deportation Flight (EN)Marianne Büttiker, Friederike Kretzen and Barbara Lüthi, “Action Black Autumn”: the Genesis of Air Deportation in Switzerland (EN)Amalia Campos-Delgado, Bordering Theatrically: Mexico Mass Expulsion of Indian Citizens (EN)Lucio Cascavilla, The Stigmata of my Deportation (EN)Aino Korvensyrjä & Rex Osa, Deportation monitoring in Germany and Nigeria: Assymetric Strategies, Solidarity and Activist Knowledge Production (EN)Clara Lecadet, Video interviews with Members of the Deportees’ Malian Association (EN – Interviews in french)Clara Lecadet and William Walters, Struggles against the “Deportation machine”: othe Anarchist Track (EN)Lesbians and Gays Support the Migrants, Dear British Airways… (EN)Maxime Maréchal, Extra-territorial voices: Language interpreting practices in the waiting zone of Roissy-Charles-de-Gaulle airport (EN)Katerina Rozakou, An Airport Ethnography of Volontary Deportations (EN)Angela Smith, Air Deportation and the Settler Colony (EN)Sarah Zellner, Frontex as a Symprom of the EU’s “Deportation Syndrome” (EN)
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".