"Penser la nation québécoise" de Michel Venne (dir.)
Bibliographic record
Abstract
Aquests dies he recordat de nou el llibre dirigit per Michel Venne (1960) Penser la nation québécoise que en el seu moment em va suscitar un gran interès i crec que mereix la nostra consideració en els temps que corren.Com segurament recorden els lectors, el Quebec va fer un nou referèndum d'autodeterminació -el darrer de moment-el 30 d'octubre de 1995, en el qual una altíssima participació del 94% del cens electoral va donar un resultat ajustadíssim: el 49,4% de vots afirmatius enfront del 50,6% de negatius.Tant sols 45.000 vots de diferència.No cal dir que la societat quebequesa va experimentar una forta sotragada en tot aquell procés i sobretot arran del desenllaç.El llibre que comentem neix de les reflexions que es van produir a partir d'aquesta forta experiència, de la voluntat d'analitzar-la i de superar-la.El periodista Michel Venne, aleshores redactor en cap adjunt del diari quebequès Le Devoir -la capçalera més seriosa i acreditada dels mitjans francòfons canadencs-va promoure una reflexió pública que encara avui em sembla un gran encert.Va convidar una quinzena de personalitats rellevants de diferents camps de la societat quebequesa (antropologia, pensament, sociologia, història, politologia, dret, política...), dins d'un ampli espec-
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".