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Record W3030836714 · doi:10.21100/jeipc.v6i1.1005

Using Basecamp in student-staff partnerships to organize, communicate, and promote non-hierarchical leadership

2020· article· en· W3030836714 on OpenAlexaff
Brandon M. Sabourin, John Freer, Isabella Bobbie, Marissa Bumanlag, Alexander Derbyshire, Liz Huntingford, Swati Sharma

Bibliographic record

VenueThe Journal of Educational Innovation Partnership and Change · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsSt. Clair CollegeUniversity of Windsor
Fundersnot available
KeywordsGeneral partnershipKnowledge managementPublic relationsBusinessPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Student-staff partnerships can benefit from using a digital project management platform tool for organization. However, implementing digital technologies in student-staff partnerships requires consideration of how such tools help to promote the values of the partnership. In this review, we explore how our research activities as members of the Partnerships for Research in Education Program (PREP) have been influenced by our adoption of Basecamp as a project management platform.

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)0.018
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0080.008
Open science0.0020.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.537
GPT teacher head0.458
Teacher spread0.078 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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