The use of conceptual and categorical apparatus in the cross-national comparative researches
Bibliographic record
Abstract
At the beginning of the XXI century a noticeable transformation of migration processes is observed under the influence of globalization, which effect the change of social, cultural, spiritual and economic models of different countries and world regions more and more actively. This stipulates the necessity for host countries to improve migration policies for more effective control over economic, social and cultural advantages or, vice versa, disadvantages, which international migration brings with it. Consequently, the necessity of constant examination of this problem seems logical, including the level of cross-national comparative researches, during which the study of the same phenomenon in two or more countries in various socio-cultural conditions with the usage of the same tools takes place. Taking into consideration the variable and unpredictable nature of the problem, the necessity of the stable basis for such researches is transparent, first of all, the need of permanent generally accepted and used conceptual and categorical apparatus, which predetermines primary importance of the research of this apparatus in the field of migration; in this context, the analysis of using of the terms “migrant” and “ethnic minority” in the scientific political and social discourses of such countries, as Canada, Great Britain and Germany is given in the case of this article. Keywords: Migration, migrant, ethnic minority, cross-national comparative researches, conceptual and categorical apparatus
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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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.039 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".