Bibliographic record
Abstract
En 2001, les Chinois formaient la minorité visible la plus importante au Canada avec plus d’un million de personnes s’identifiant comme telles. La question se pose de plus en plus quant à savoir jusqu’où les Chinois et d’autres membres de groupes minoritaires peuvent s’ajuster et s’assimiler à la société majoritaire. Cependant, il n’existe pour le moment aucun instrument utilisable pour mesurer les niveaux d’acculturation des Chinois résidant au Canada. Cet article en présente un spécifiquement conçu pour ces derniers. Il porte sur sept aspects à évaluer : interactions sociales, préférence langagière, perception de soi, identité ethnique, présentation de cadeaux et célébration de fêtes, nourriture et préférence communautaire, ainsi que piété filiale. Cette approche fournit des données mesurables quant au contenu, à leur fonction discriminante, et à leur validité prédictive ainsi qu’un haut degré de fiabilité. Mais il ne faut pas ignorer les limitations de cette recherche, ni les besoin d’une autre à venir.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".