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Record W1517321736 · doi:10.19173/irrodl.v13i2.1122

Educational leadership for e-learning in the healthcare workplace

2012· article· en· W1517321736 on OpenAlexaffvenue
Dorothy Fahlman

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsAthabasca University
Fundersnot available
KeywordsEducational leadershipServant leadershipDistributed leadershipBridge (graph theory)NeuroleadershipHealth careWorkplace learningShared leadershipKnowledge managementPublic relationsStrategic leadershipHealth professionalsPsychologyBusinessMedical educationSociologyLeadership stylePedagogyPolitical scienceComputer scienceMedicineEngineering

Abstract

fetched live from OpenAlex

Effective educational leadership can make a difference in the resolution of complex issues that impact today’s demand-driven educational marketplace. The ongoing professional and skill development needs of human health resources may be best managed through distributed strategic leadership blended with servant leadership. Together these two approaches may offer the critical bridge for effective educational leadership for e-learning within the healthcare workplace.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.226
GPT teacher head0.434
Teacher spread0.208 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations13
Published2012
Admission routes2
Has abstractyes

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