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Record W2913448506 · doi:10.15402/esj.v4i1.318

Imagination Practices and Community-Based Learning

2018· article· en· W2913448506 on OpenAlexvenueno aff
Simone Weil Davis

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsScrutinyActive listeningConstruct (python library)Service-learningSociologyLearning communitySpace (punctuation)Community buildingEquity (law)PedagogyPublic relationsPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

Informed by my experiences in prison/university co-learning projects, this essay centres two community-based learning practices worth cultivating. First, what can happen when all participants truly prioritize what it means to build community as they address their shared project, co-discovering new ways of being and doing together, listening receptively and speaking authentically? How can project facilitators step beyond prescribed roles embedded in the charity paradigm of service-learning to invite and support egalitarian community and equity-driven decision-making from a project’s inception and development, through its unfolding and its assessment? Second, the sheer fact of a project taking place in the marginal place between two contexts gives all participants—students, faculty, community participants and hosts—the opportunity for meta-reflection on the institutional logics that construct and constrain our perspectives so acutely. What can we do, by way of project-conception and pedagogy, to open up those insights? The vantage that “the space between” provides can bring fresh understanding of the systemic forces at work in the lives of the community participants. And the university’s assumptions about itself and its place in the world can also suddenly appear strange and new, objects of scrutiny for students and community members both.

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)0.912
metaresearch head score (Gemma)0.770
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9120.770
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.8120.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0000.796
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 head0.227
GPT teacher head0.461
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; both teacher heads agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations2
Published2018
Admission routes1
Has abstractyes

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