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Record W4400692120 · doi:10.1021/acs.jchemed.3c01321

Toward Collaborative Dialogue: Unpacking the Researcher–Educator Divide to Advance Chemistry Education

2024· article· en· W4400692120 on OpenAlex
Nicole M. James, Myriam S. McKenna, Aakash Mishra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chemical Education · 2024
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLeverage (statistics)UnpackingChemistry educationRepresentation (politics)Engineering ethicsPedagogySociologyChemistryMathematics educationPolitical sciencePsychologyComputer scienceEngineeringPoliticsSocial psychology

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Researchers, educators, and students have different roles in the chemistry education community and are subject to distinct evaluation criteria that inform how they approach their work. In this commentary, we leverage our experience as individuals positioned at the researcher–educator–student interface to describe how we consider these evaluation criteria to incentivize different priorities. These priorities often align synergistically but sometimes conflict. We argue that conflicts between priorities can lead to divisions among community members that undermine the achievement of our shared goals. Based on this understanding, we suggest examples of how the community might overcome these challenges by facilitating education research knowledge mobilization, expanding representation of chemistry education at the undergraduate level, and engaging in collaborative dialogue.

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.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.366
Teacher spread0.341 · 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