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Record W181455158

Community capacity building: lessons from adult learning in Australia

2014· article· en· W181455158 on OpenAlexaboutno aff
Glen Postle, Lorelle J. Burton, Patrick Alan Danaher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsCapacity buildingFutures contractAction (physics)Community buildingResource (disambiguation)Community of practicePolitical scienceCommunity developmentSociologyPedagogyBusiness
DOInot available

Abstract

fetched live from OpenAlex

Across multiple disciplines concerned with community development there is growing interest in the phenomenon of community capacity building; activities, resources and support strengthening the abilities and skills of individuals and groups to take action and to lead the development of their own communities. This book is a valuable resource that presents the latest research into the social and educational issues involved and offers new insights into effective strategies and outcomes for both specific and global communities. Through experiences in Australia and drawing on examples of good practice internationally (including the UK, US, Canada, Europe and New Zealand), the contributors, themselves a mixture of academic researchers and community members, examine with great breadth and depth how regional and rural communities sustain themselves for equitable and prosperous futures and how community members and university academics can create useful knowledge together. This text uniquely brings community capacity building to life through the personal involvement of academic staff in the community as active partners helping to create new knowledge.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.170
GPT teacher head0.430
Teacher spread0.259 · 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 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

Citations15
Published2014
Admission routes1
Has abstractyes

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