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Record W6907950410 · doi:10.25384/sage.c.5975801

Fostering Learning and Reciprocity in Interdisciplinary Research

2022· other· en· W6907950410 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReflexivityReciprocity (cultural anthropology)Process (computing)Participatory action researchCitizen journalismExperiential learning

Abstract

fetched live from OpenAlex

While cohesive teams are essential to advancing interdisciplinary research, few frameworks exist to guide team development. In this article, eight academic women adopt a participatory process of inter-relational reflexivity to reflect upon our interdisciplinary research and propose a best-practice framework for sustained effectiveness of interdisciplinary collaboration.

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)0.280
metaresearch head score (Gemma)0.310
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.888

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2800.310
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0180.055
Scholarly communication0.0210.018
Open science0.0050.059
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.002

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 head0.290
GPT teacher head0.494
Teacher spread0.204 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207