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Towards More Socio-Culturally Sensitive Research and Study of Workplace E-Learning

2014· book-chapter· en· W4236339405 on OpenAlexaff
Karim A. Remtulla

Bibliographic record

VenueIGI Global eBooks · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWorkplace learningAdult educationPedagogySpace (punctuation)Adult LearningPsychologySociologyPublic relationsWork (physics)Political scienceEngineering

Abstract

fetched live from OpenAlex

This article advocates workplace adult education and training researchers and scholar practitioners interested in career and technical education (CTE), adult education and technology, and who are attempting social and cultural critiques of workplace e-learning. The emphasis on the technological and artefactual in workplace e-learning research and study are not producing the expected learning outcomes from workplace adult education and training to the degree anticipated. Given increasingly global and diverse workforces, the research and study of workplace e-learning as a socio-culturally ‘negotiated' space may be an alternate approach toward a more socially and culturally informed understanding of adult learning from workplace e-learning.

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)0.006
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.020
Scholarly communication0.0100.009
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.096
GPT teacher head0.426
Teacher spread0.330 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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