Bibliographic record
Abstract
Ce livre n’est pas un reportage sur le tremblement de terre d’Haiti mais un recueil de courts textes que cet evenement a suscite chez l’auteur. Sur le calepin noir dont il ne se separe jamais, il note sur le vif, la peur, l’hebetude, l’angoisse, les cris, le silence, l’urgence, la recherche des proches... Rapatrie trois jours plus tard au Canada, il continuera a vivre cette catastrophe non plus comme temoin direct mais comme le reste du monde a travers les images televisees qui tout d’abord lui revelent l’ampleur du drame. Ce sera un deuxieme choc. D’autres reflexions en resulteront notamment sur le fonctionnement des medias qui abusent de lieux communs si faciles a vehiculer, qui propagent des rumeurs, qui parlent de maledictions. En depit de cyclones frequents, d’inondations devastatrices et des longues annees de dictature, Haiti n’est pas une ile maudite. C’est une terre avec un peuple qui a une culture, une histoire, une langue, des peintres, des artistes, des poetes.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.090 | 0.026 |
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".