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Record W4248120936 · doi:10.32920/ryerson.14662899.v1

Navigating community-engaged scholarship within neoliberal academic institutions

2021· preprint· en· W4248120936 on OpenAlexaff
Rebecca Pacheco

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsToronto Metropolitan UniversityCentre for Social InnovationUniversity of Waterloo
FundersStrong
KeywordsScholarshipInstitutionContext (archaeology)Public relationsEngaged scholarshipSociologyWork (physics)Academic communityCommunity engagementPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The overall purpose of this research was to identify systemic conditions within academia that are preventing researchers from engaging in CES, and ultimately, influence change in university policies and procedures pertaining to community-based research. Using interpretive phenomenological inquiry, four community-engaged social work scholars were interviewed about their experience with participating in community-engaged research. The interviews explored the experiences of community-engaged scholarships within the current academic context, and how their work is valued, recognized and rewarded by their academic institution. It was found that the participants had a common understanding that community-engaged scholarship and its research outcomes remain largely undervalued by the majority of academia. The participants provided many of their own personal experiences while also pointing out restrictive policies and practices at their university. The implications of these trends are discussed and entry points for change in the academy are highlighted.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0300.051
Scholarly communication0.0260.014
Open science0.0050.048
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.249
GPT teacher head0.435
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainEvaluation
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

Citations0
Published2021
Admission routes1
Has abstractyes

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