Bibliographic record
Abstract
Les Mi’gmaq (Mi’kmaq) sont présents au Québec, dans toutes les provinces maritimes et même dans l’État du Maine aux États-Unis. Ils forment une population de plus de 50 000 individus, dont environ 7 000 au Québec. Traditionnellement, le territoire mi’gmaq était constitué de sept districts, dont celui de Gespegeoag qui correspond aujourd’hui à la péninsule gaspésienne et qui abrite trois communautés : Listuguj, Gesgapegiag et Gespeg. Ce qui distingue le plus cette nation des autres peuples algonquiens du Québec est sans doute la proximité de la mer qui imprègne toute la vie économique et culturelle de ses membres. C’est donc dire l’extrême importance de la pêche, hier et aujourd’hui, dans cette société. Avant le contact, les Mi’gmaq subsistaient grâce aux activités cynégétiques et halieutiques, la cueillette complétant le tout. Ils cultivaient aussi le tabac. Le recueil de récits qui leur est consacré reflète ce mode de vie ancestral et se veut une contribution à la connaissance de ce peuple aux héros multiples et vivaces qui sauront en étonner plusieurs. Daniel Clément a gagné le prix Mnémo 2020 pour la série "Les récits de notre terre".
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.010 |
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".