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Record W7133377938

Community-Based Adult Learning Research in Australia and Canada: A Review Essay

2016· article· en· W7133377938 on OpenAlexaboutno aff

Bibliographic record

VenueRUNE (Research UNE) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionField (mathematics)Work (physics)Reflection (computer programming)Adult Learning
DOInot available

Abstract

fetched live from OpenAlex

From opposite sides of the world, scholars in two universities have produced books that reflect on the adult learning involved when universities undertake community-based research. Each book combines case studies of actual projects with some reflection on the nature of this work as a distinct field of research practice within universities of the Global North. In Australia, the researchers were located in the rural city of Toowoomba, on a campus of the University of Southern Queensland, while in Canada, the host institution was the University of Victoria in British Colombia. The editors of both collections argue strongly for the importance of community-based research, and they locate their initiatives in a global trend toward greater engagement between universities and the specific geographical locations in which they are situated.

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)0.007
metaresearch head score (Gemma)0.015
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: Review · Consensus signal: Review
Teacher disagreement score0.283
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.019
Science and technology studies0.0050.005
Scholarly communication0.0090.004
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.327
GPT teacher head0.486
Teacher spread0.159 · 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
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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