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Foreigners in the Polish Academic System at the Beginning of the 21st Century. A Quantitative Analysis of Their Employment According to the Official Documents

2014· article· en· W793223501 sur OpenAlex

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Notice bibliographique

RevuePolish Sociological Review · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueSocial Issues in Poland
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)PrestigeChristian ministrySociologyHigher educationPolitical scienceMinistry of Foreign AffairsSocial scienceLawHistoryLinguistics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Abstract: This is an empirical quantitative analysis of the official data coming from the Polish Ministry of Science and Higher Education. The foreign scholars in Poland at the beginning of the 21st century are presented in the context of the global circulation or migration of highly qualified specialists. The second context is the present Polish academic system. In this paper we discuss characteristics of the analysed data base, universities and colleges where the foreign scholars are usually employed, the academic disciplines they represent, the relations between the number of foreign scholars and the institutional prestige of schools employing them, and conclusions on what we can and cannot learn from the data set analysed here.Keywords: Brain circulation, migrations of scholars, academic system in Poland, foreign scholars in Poland.IntroductionThe following is the empirical analysis of the official database provided by the Polish Ministry of Science and Higher Education at the end of 2012. The Ministry obtained this information from individual Polish research and higher education institutions and then aggregated it. This article shows, only from a quantitative perspective, the population of foreigners who are employed in the Polish academic system. We do not use any other data sets (although, we offer our own typologies, comparisons with other aggregated databases and the breakdowns which are not present in the original database, where we find possible). Despite the minuteness of individual pieces of information, the base proves to be an estimate rather than one of precise character. However, this is the most comprehensive set of official Polish data on the topic. We believe that it is better to analyse this imprecise base than to ignore it altogether. The problem is that due to its inaccurate character, it is very difficult to test more general hypotheses. Therefore, our interpretations cannot be anything other than relatively soft.We begin with the general social context of the local Polish circulation. This context is formed by the contemporary migrations of highly skilled specialists, and particularly by the recent globalization of the world of research and higher education (for a summary, see, e.g., Mucha 2013). The second context is the Polish academic system.Brain circulationForeigners have been a crucial element in many academic systems for many centuries. However, in this article we are interested in the most recent situation. We have found selected global information from 2001 (eleven years earlier than the data base we are analysing now was compiled). In the ten leading countries of Europe and the US, the proportion of foreigners was as follows: Switzerland-13.0%; the US-8.9%; United Kingdom-5.9%; Norway-4.3%; Belgium-3.3%; Austria-3.0%; France-2.8%; Germany-2.8%; the Netherlands-1.6% and in Italy-0.3% (see: Kaczmarczyk and Okolski 2005:51, Table 8). The first of these selected countries enjoyed the proportion of researchers and academic teachers coming from abroad more than forty times higher than the tenth country; the second had this proportion thirty times higher that the tenth. In the US (the most studied country), the foreigners work first of all in the most prestigious research universities, mainly in departments of science and engineering. In some of these disciplines, every third newly employed scientists is a foreigner. In the same country, in the early 21st century, most foreign researchers and academic teachers came from China (22%), India (9,4%), South Korea (9,3%), Japan (5,4%), Germany (5%) and Canada (4,5%). From 1965 on, most immigrant scientists have come from non-European regions, such as Asia, Africa and South America (Kim, Wolf-Wendel and Twombly 2011: 721).Migrations of scientists (and, more broadly, of highly skilled specialists) are often analysed in terms of brain drain. This concept (and its transformations) is very useful if we want to briefly present various phenomena characterizing the multifaceted and multidirectional migrations of scientists in a world which is far from equilibrium, a world in which centres, semi-peripheries and peripheries are shifting all the time, and one in which individual countries have various interests related to the production of knowledge. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,701
Score d'incertitude au seuil0,657

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0080,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,002
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0020,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,076
Tête enseignante GPT0,414
Écart entre enseignants0,338 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle