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From Lancelot to Lapland: Implications of Engaged Rural Universities

2016· book-chapter· en· W2576606431 on OpenAlexaboutno aff
Heidi Hodge, Dean B. Carson, Peter Berggren, Roger Strasser

Bibliographic record

VenueInnovations in higher education teaching and learning · 2016
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsReciprocalFunction (biology)Rural historyPublic relationsRural areaPolitical scienceSociologyLibrary science

Abstract

fetched live from OpenAlex

This chapter examines the extent to which place based and research oriented university-community engagement (UCE) models can sustain UCE in “non-campus” rural settings. It examines how effective partnerships function in non-campus rural settings, and their contributions to achieving the reciprocal aims of communities and universities. It highlights the key successes, challenges, and opportunities experienced through case studies in non-campus locations in rural Australia (Flinders University Rural Clinical School), rural Sweden (Centre for Rural Health, Storuman), and rural Canada (Northern Ontario School of Medicine). Information provided about the discussed case studies has been provided by the organizations themselves, and the chapter authors are heads of these organizations. The authors share their knowledge of the history, the challenges, the opportunities, and the mechanisms through which the models interact with the partners.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.059
GPT teacher head0.406
Teacher spread0.347 · 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.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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