The Refugee’s Body of Knowledge: Storytelling and Silence in the work of Francisco-Fernando
Bibliographic record
Abstract
This paper begins by considering the negative implications of recent amendments to the refugee certification process in Canada. It foregrounds the waning impor-tance of narrative in that process and then asks what is lost when refugees are denied the opportunity to tell their stories in meaningful and politically expedient forums. The second half of the article attempts to answer that question by draw-ing on the scholarship and artistic practice of Francisco-Fernando Granados, a Guatemalan-Canadian performance artist and refugee whose work seeks to expand the kinds of stories refugees are invited to tell, whether in the courtroom, on the stage, or on the page. RÉSUMÉ Cet article commence en considérant les conséquences négatives des amendements récents au processus d’évaluation des demandes d’asile. Il met au premier plan la diminution de l’importance du récit au sein du processus et pose la question de ce que l’on perd lorsque les réfugiés sont refusés l’occasion de raconter leurs histoires dans des forums officiels et stratégiques sur le plan politique. Dans un deuxième temps, l’article tente de répondre à cette question en s’appuyant sur les recherches et la pratique artistique de Francisco-Fernando Granados, un artiste de performance et réfugié guatémalien-canadien à qui le travail cherche à élargir la variété d’histoires que les réfugiés sont invités à raconter, que ce soit dans une salle d’audience, sur la scène, ou sur la page.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.044 | 0.060 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".