MétaCan
Menu
Back to cohort
Record W1583982878 · doi:10.5539/ies.v8n6p217

Historiography of Developing the Issue of the Information Skills in the Social and Cultural Space of the Further Education

2015· article· en· W1583982878 on OpenAlexvenueno aff
Kucher Tatyana Pavlovna, Kolyeva Natalya Stanislavovna

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsHistoriographySociologyCompetence (human resources)Social scienceConceptual frameworkCultural analysisEpistemologyPhenomenonSocial competencePedagogyEngineering ethicsPsychologySocial psychologySocial changePolitical science

Abstract

fetched live from OpenAlex

The paper deals with the problem of historiography, presented in three stages: the first stage (50-90s of the ХХ century) is characterized by the introduction of a scientific apparatus expertise creating the preconditions of differences between concepts, the release of an independent direction of history of social and cultural activities. In the second phase (90-2000s) pedagogical research appears on the problem of the formation of different types of competence (professional, informational, social, psychological, communication, legal, social, cultural and educational). The methodology of historical and educational research created and refined conceptual framework of social and cultural activities. The third phase (2000 to the present) is characterized by comprehensive research in the field of information competence, substantiation of theoretical and methodological framework, the researchers conducted an analysis of the phenomenon of leisure activities from the standpoint of the theory of culture, an emphasis on cultural needs, which are the motivation for leisure-time activities.

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: none
Teacher disagreement score0.009
Threshold uncertainty score0.036

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 studies0.0020.007
Scholarly communication0.0030.004
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.090
GPT teacher head0.456
Teacher spread0.366 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Education StudiesSame topicEducational Practices and ChallengesFrench-language works237,207