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DENTAL EDUCATION IN THE ARCTIC COUNTRIES

2024· article· en· W4401325903 on OpenAlexaboutno aff
Yuliya Kalinina

Bibliographic record

VenueJournal of Pedagogical Studies · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticGeographyOceanographyGeology

Abstract

fetched live from OpenAlex

The structures of dental education in near-Arctic countries and regions at all levels are considered and the place of the pedagogical component is increased in them. It was noted that the actively functioning structures of additional vocational education (DPO) in 8 countries of the Arctic Council (Denmark, Iceland, Canada, Norway, the Russian Federation, the USA, Finland, Sweden) determine the dynamics of the assimilation by practicing dentists and maxillofacial surgeons of the use of the latest high-tech technologies, and in recent decades also a complex of humanities, primarily psychology and sociology. This increases the role of the pedagogical component in the system of their professional training of dentists and maxillofacial surgeons; the experience of organizing training processes in this direction is also in demand by the structures of domestic dental education. Its parameters are characterized taking into account the specifics of the Arctic zone, including ensuring the health of teeth and oral cavity of representatives of small indigenous peoples; problems of staffing of dentists and maxillofacial surgeons and improvement of their qualification level are analyzed. Due to the coordination of educational and research activities, the postgraduate education system is characterized by the transfer of the latest skills and techniques in dental education.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.357
GPT teacher head0.644
Teacher spread0.287 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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