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Record W7035834739

Advancements in Work-Integrated Learning Research: Editorial Insights

2024· article· en· W7035834739 on OpenAlexfundno aff

Bibliographic record

VenueTuwhera (Auckland University of Technology) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
FundersCollege of Engineering, Michigan State UniversityMichigan State UniversityFlinders UniversityUniversity of TorontoUniversity of SurreyUniversity of WaterlooCurtin University of TechnologyUniversity of the Sunshine CoastUniversity of New South WalesAuckland University of Technology, New ZealandUniversity of WollongongUniversity of Waikato
KeywordsScholarshipTransformative learningPromotion (chess)StakeholderEngaged scholarshipEquity (law)
DOInot available

Abstract

fetched live from OpenAlex

Over the past two decades, scholarship into work-integrated learning (WIL) has significantly expanded, highlighting the importance of its contribution to higher education. The International Journal of Work-Integrated Learning (IJWIL) has been an important part of the promotion of research and scholarship of WIL, and the dissemination of new knowledge. This current IJWIL Issue includes three articles that provide a bibliometric analysis of what is now a significant body of WIL literature. These analyses reveal trends in themes such as equity and access, professional identity development, stakeholder engagement, risks, and highlight the high level of collaboration among WIL researchers. This editorial emphasizes the advances of WIL scholarship by further identifying key developments and topical challenges and linking these to recent published WIL literature to inspire further research to enhance the understanding of WIL as a transformative pedagogy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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