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Record W3211863712 · doi:10.54590/pop.2021.002

Enabling Public Scholars through Faculty Development

2021· article· en· W3211863712 on OpenAlexvenueno aff
Christopher Adamson

Bibliographic record

VenuePop! Public Open Participatory · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPublic relationsSociologyGeneral partnershipFaculty developmentEngaged scholarshipDialogical selfPolitical scienceWork (physics)Community engagementPedagogyMedical educationProfessional developmentPsychologyEngineeringMedicine

Abstract

fetched live from OpenAlex

To support faculty as they remained civically engaged during the pandemic, the Center for Teaching and Learning at the University of South Dakota (CTL) launched a training series on public scholarship partnering with facilitators from Emory, Baylor, and Harvard. Core outcome of the series were for faculty to find a home for themselves in public engagement and to support students in their own public-facing work. The series introduced faculty to public scholarship as a dialogical partnership and offered workshops on facilitating public-facing student work and organizing virtual conferences, concluding each term with a panel featuring academics who promote the common good in different ways. This article explains the development of this series with the theoretical underpinnings that guided it and concludes by proposing a definition of public scholarship that includes student voices and repositions universities within the communities they inhabit.

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)0.029
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0170.025
Scholarly communication0.0240.020
Open science0.0040.062
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0270.005

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 head0.541
GPT teacher head0.493
Teacher spread0.048 · 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 designQualitative
DomainIncentives
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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