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Record W2151666082 · doi:10.21225/d5mk5f

Reframing University Continuing Education’s Role in Community Engagement

2012· article· en· W2151666082 on OpenAlexaffvenueabout
Heather McRae

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCognitive reframingCommunity engagementHigher educationInstitutionSociologyStudent engagementPublic relationsPublic engagementUnit (ring theory)Work (physics)PedagogyPolitical sciencePsychologySocial scienceEngineering

Abstract

fetched live from OpenAlex

In Canada, a growing interest within higher education in community engagement practices is evidenced through the establishment of national networks, funding opportunities for community-university research partnerships, and the development of specially designated centres on university campuses. However, based on the literature in continuing education, the role of university continuing education (UCE) units in supporting community engagement is not clear. Many UCE units have been involved and continue to be involved in developing and implementing various types of community engagement activities, yet the work of these units is not widely recognized within the university and the community as contributing substantially to the social purpose mission of the institution. The pressures and tensions relating to balancing the social and economic goals of the UCE unit may be influencing the role of UCE in community engagement. Strategies identified in this article that could assist UCE in embedding community engagement within the practice and in reframing the focus of UCE include the development of a community engagement framework and measurement tools that assess outcomes leading to positive social change.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.255
Teacher spread0.234 · 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 designQualitative
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

Citations3
Published2012
Admission routes3
Has abstractyes

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