Bibliographic record
Abstract
Un apres-midi d’ete, l’ecrivain croise sur la rue Saint-Denis un jeune homme, Mongo, qui vient de debarquer a Montreal. Il lui rappelle cet autre jeune homme arrive dans la meme ville en 1976. Le meme desarroi et la meme determination. Mongo demande : comment faire pour s’inserer dans cette nouvelle societe ? Ils entrent dans un cafe et la conversation debute comme dans un roman de Diderot. C’est ce ton leger et grave que le lecteur reconnait des le debut d’un livre de Laferriere:« Tout nouveau-ne est un immigre qui doit apprendre pour survivre les codes sociaux. Une societe ne livre ses mysteres qu’a ceux qui cherchent a la comprendre, et personne n’echappe a cette regle implacable, qu’on soit du pays ou non.» Laferriere raconte ici quarante annees de vie au Quebec. Une longue lettre d'amour au Quebec.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".