Bibliographic record
Abstract
L’Africa subsahariana es un subcontinent d’emigracio1 per excel·lencia. Des de fa diverses decades,2 aquesta regio va coneixer migracions de naturalesa diversa i de destinacions diferents. A mitjan i a la fi dels anys 80, va apareixer un flux migratori mes intens, orientat cap al que els estudiosos van anomenar els “nous destins”: alguns paisos de l’Africa central, d’Europa, d’America i d’Oceania. Aquest flux cap a “nous destins” va ser influenciat pels efectes desastrosos d’una serie de crisis economiques sense precedents. Aquesta fase va ser coneguda com l’explosio o la multipolaritzacio migratoria (Robin, 1966). El camp migratori africa s’estengue rapidament cap a Costa d’Ivori, l’Africa central (ambdos Congos), Angola i els paisos del golf de Guinea. De l’Africa, els nous candidats a l’emigracio n’intentaren “conquerir” allo que els analistes van anomenar “el nou mon migratori”. Els vells destins van ser gairebe abandonats en detriment d’altres. Els Estats Units, el Canada, el Japo, Taiwan, Australia, Tailandia, Alemanya, els paisos del golf Persic, Portugal, Italia, Grecia, Espanya... van irrompre, aixi, en el camp migratori dels africans.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".