Instrumentalizarea spațiilor virtuale. Noi strategii de reproducere și conversie a capitalurilor în situație migratorie
Bibliographic record
Abstract
The extending of NTIC on a large scale implies, at the level of international migrations, new strategies of social and geo¬graphic movement as well as big changes of the social behaviour linked to the resource display in the migration context. Starting from the example of a virtual space which represents the crossing of migration, ethnical and professional networks, this article illustrates the usage of virtual space by a particular population of highly qualified migrants - the IT professionals power: theoretical and development issues, in Migration and Development, Ed. R.T. Aplleyard, Paris, OECD, pp.109-128, empirically stressing the case of computer specialists having emigrated to Toronto. We are going to question the renewing role these migrants assume through the human, cultural and social capital with which they were originally endowed. The virtual space, with its associative power, becomes a social space of recognition, of resource investment and of identity building. Support of capital transfer, reproduction and conversion in a migratory context, this technological environment provides creative instruments for diaspora and community organization.
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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 | 0.002 | 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 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".