Bibliographic record
Abstract
France is a society where ethnic minorities try individually to integrate itself into mainstream society rather than exist as a separated group, differently with countries such as Canada and Australia where the multiculturalism has developed. Therefore this country has not been a society having conditions suitable for multiculturalism based on the recognition of ethnic mi￢nority culture as collective rights. But since the ban on employment-based immigration in 1974 which caused unexpected results of sedentarization, has come to the fore the existence of ethnic minorities especially those of non_european origin, having difficulties of integration and consequently living together in an isolated area. It’s in this context that multiculturalism emerged recently in French society. But multiculturalism have had a hard time being recognized in French society which emphasizes a homogeneity as a citizen more than a recognition of ethnic heterogeneity. Also, it takes the form of ‘interculturalism’ which considers a concrete interculturalism as an essence of culture, differently with anglo-saxon multicultural￢ism which is limited to the recognition of distinguished individual cultures regarded as a fixed one. For example, ‘intercultural education’ focuses on the multiculturality which is experienced in everyday life such as diverse forms of intenactions with their classmates and teachers the students from immigrant families practice in the school. The French immigration policy of the early 2000 is too complex to be explained simply by the dichotomy of republicanism versus multiculturalism.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".