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Record W1552681039

Rhetorical Strategies of the Postsecondary Community Service-Learning Movement in Canada

2012· article· en· W1552681039 on OpenAlexaboutno aff
Tania Smith

Bibliographic record

VenuePartnerships · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsRhetorical questionService-learningPublic relationsContext (archaeology)SociologyService (business)Social movementMovement (music)Political sciencePoliticsPedagogyLinguisticsBusinessHistoryLawAestheticsMarketing
DOInot available

Abstract

fetched live from OpenAlex

This article analyzes the rhetorical strategies of the community service-learning movement in Canada, offering a description of the movement that is accessible to both Canadian and international readers who are familiar with service-learning. The article first provides a general comparison of the context, features and progress of the Canadian community service-learning (CSL) movement in light of the American service-learning movement. It then it analyzes the unique messages and features of the Canadian movement using social movement theory and rhetorical theory as a frame. It concludes with recommendations regarding the rhetorical strategies and organizational structures that are likely to be ethical and effective in forwarding the CSL initiative in Canada and adapting it to the unique cultural, social and political contexts of its higher education system. These insights are offered from the perspective of a Canadian faculty member from the discipline of rhetorical studies who teaches, researches, and leads in the movement both nationally and locally. KEYWORDS service-learning; social movements; higher education; institutionalization; community partnerships

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.127
GPT teacher head0.315
Teacher spread0.188 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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