Migration and Skills : The Experience of Migrant Workers from Albania, Egypt, Moldova, and Tunisia
Notice bibliographique
Résumé
The subject of migration, and how best to manage it, has been moving up the policy agenda of the European Union for some time now. Faced with an aging population, possible skills shortages at all skills levels, and the need to compete for highly skilled migrants with countries such as Australia, Canada, and the United States, the European Union (EU) is moving from seeing migration as a problem or a threat to viewing it as an opportunity. As an EU agency promoting skills and human capital development in transition and developing countries, the European Training Foundation (ETF) wished to explore the impact of migration on skills development, with a special emphasis on Diasporas and returning migrants. For the World Bank, the issue of migration forms an integral part of its approach to social protection, since it believes that labor-market policy must take into account the national as well the international dimensions of skilled labor mobility. Both institutions were keen to look at what changes need to be made to migration policy in order to achieve a triple-win situation, one that can benefit both sending and receiving countries as well as the migrants themselves. This report aims to unravel the complex relationship between migration and skills development. It paints a precise picture of potential and returning migrants from four very different countries, Albania, the Arab Republic of Egypt, Moldova, and Tunisia, that is a conscious choice of two 'traditional' (Egypt, Tunisia) and two 'new' (Albania, Moldova) sending countries, and describes the skills they possess and the impact that the experience of migration has on their skills development. It is harder to draw accurate conclusions on the link between job aspirations and current employment status, since many of the potential migrants were not actively employed at the time of the interview. However, the data suggest people did expect to change jobs as a result of migration, and the sectors they expected to work in varied according to their nationality. Focusing solely on those planning to move to the EU, many Albanians expected to work in domestic service, hospitality, and construction; Egyptians expected to work in hospitality and construction; Moldovans expected to work in domestic service and construction; and Tunisians expected to work in hospitality and manufacturing. Few migrants working in agriculture or petty trade aimed to work in these same sectors while abroad.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,021 | 0,006 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».