MétaCan
Menu
Back to cohort
Record W793223501

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 on OpenAlexaboutno aff
Janusz Mucha, Kamil Łuczaj

Bibliographic record

VenuePolish Sociological Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Issues in Poland
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PrestigeChristian ministrySociologyHigher educationPolitical scienceMinistry of Foreign AffairsSocial scienceLawHistoryLinguistics
DOInot available

Abstract

fetched live from 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. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.076
GPT teacher head0.414
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePolish Sociological ReviewSame topicSocial Issues in PolandFrench-language works237,207