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Record W4401485857 · doi:10.1177/14761270241274038

Communities for impact: Empowering early-career researchers in the pursuit of impact

2024· article· en· W4401485857 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStrategic Organization · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsWestern UniversityBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPublic relationsNarrativeSociologyPolitical scienceCareer developmentPedagogy

Abstract

fetched live from OpenAlex

Impact-driven early-career researchers are conducting research that matters and generating insights that help tackle grand challenges. While this group is passionate about transforming organizations and society, these researchers tend to be held back by institutional barriers and to be marginalized in academia. We propose the concept communities for impact as spaces to help researchers (especially early-career researchers) cope with the challenges of impact-driven research. These communities can give their members a voice, legitimate their actions, and provide resources for unleashing the impact potential of their research. Communities for impact may be able to mitigate the uncertainties and challenges experienced by early-career researchers, but they cannot eliminate persistent institutional barriers. Therefore, we invite scholars at all career stages to join a community for impact to help change the narrative and empower early-career researchers to meaningfully address grand challenges.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.771
GPT teacher head0.692
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