MétaCan
Menu
Back to cohort
Record W2163722333 · doi:10.5539/res.v7n5p47

The Distinctive Features of a Picture of the World of the Students of Pharmaceutical Faculty

2015· article· en· W2163722333 on OpenAlexvenueno aff
Ildar R. Abitov

Bibliographic record

VenueReview of European Studies · 2015
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Teacher Development
Canadian institutionsnot available
FundersKazan Federal University
KeywordsValue (mathematics)Relevance (law)PharmacyLuckGoodwillPsychologyPublic relationsSpecialtyWork (physics)SociologyEngineering ethicsMedical educationPolitical scienceBusinessMedicineLawAccountingEpistemologyEngineeringPsychiatryComputer science

Abstract

fetched live from OpenAlex

The relevance of the studied problem is caused by the lack of the uniform model of a picture of the world of the professional and the insufficient number of the researches of a picture of the world of the pharmacists. The purpose of this article is the acquaintance of the psychologists working in the educational institutions and the pharmaceutical companies with the results of the research of a picture of the world of the students of the pharmaceutical faculty of medical school, which work in the specialty. The main result of this research is the empirical confirmation of the model of the picture of the world that includes the belief about the goodwill and justice of the world around, the one’s own value and importance, the luck and ability to control the events of the life, about the future and about the efficiency of the professional activity. The materials of the article can be useful for the psychologists of the educational institutions in which there are pharmaceutical faculties, and also for the psychologists working in the pharmaceutical companies and pharmacy chains.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.005
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.192
GPT teacher head0.466
Teacher spread0.274 · 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 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueReview of European StudiesSame topicEducational Methods and Teacher DevelopmentFrench-language works237,207