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DEVELOPMENT OF HIGHER MEDICAL EDUCATION ABROAD IN THE STUDIES OF UKRAINIAN COMPARATIVISTS

2024· article· en· W4404228987 on OpenAlexaboutno aff
Ольга Снітовська

Bibliographic record

VenueМедична освіта · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianPolitical scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

The article presents a synthesized historiographical analysis of Ukrainian pedagogical comparativistsʼ works on the development of higher medical education in foreign countries, identifying trends, achievements, bottlenecks, and prospects for studying this problem. The presented sample of dissertations, monographs, and textbooks demonstrated their narrow country-specific vector and similarity in formulating the subject of research. Historiographical and comparative analysis revealed similar approaches of scientists to determining trends in the development and functioning of national systems of professional training for doctors. These concern the preservation and expansion of decentralization in higher medical education management; strengthening the interaction of its various links; shifting emphasis in determining the prerequisites for the development of national higher medical education systems from “traditional” factors (political, socio-economic, cultural situation of the country, etc.) to clarifying the influences of international medical organizations and documents in the field of healthcare that substantiate general strategies for training doctors in higher medical education institutions, etc. Scientists also propose original approaches to studying the functioning of national systems of higher medical education. These are manifested in the development of authors periodizations and classifications of the specified process; thorough characteristics of university environments for training future doctors in different countries; comprehensive understanding of the determinants of their formation and development, which, in addition to social, economic, and cultural factors of the country's development, relate to the level of education of the population, its multiculturalism, the specifics of educational systems, etc. In these perspectives, the analyzed studies mark two main country-specific vectors of research in higher medical education: “overseas” (USA and Canada) and “European” (mainly Great Britain, Poland, and German-speaking countries).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.004
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.128
GPT teacher head0.463
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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