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Record W4416715853 · doi:10.1080/14767333.2025.2592932

Effectuation, stalled: action learning and the Commitment Readiness Gap for creative entrepreneurs

2025· article· en· W4416715853 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.

Bibliographic record

VenueAction Learning Research and Practice · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsMount Royal University
Fundersnot available
KeywordsAction learningExperiential learningAction (physics)Work (physics)Reflective practiceEntrepreneurship

Abstract

fetched live from OpenAlex

Early-stage creative entrepreneurs (CEs) often bring strong skills and compelling visions, yet their ventures stall before building real momentum. This qualitative study followed six such entrepreneurs over a ten-week Action Reflection Learning (ARL) programme, using session recordings, artefacts, and journal notes, and analysed them thematically to explore how reflection is converted into actionable commitments. Participants were introduced to effectuation, a decision-making logic used by expert entrepreneurs, as practical heuristics for acting under uncertainty. Although effectuation is widely used to teach novice entrepreneurs, participants experienced multiple points of stall, revealing a Commitment Readiness Gap. The ARL programme helped bridge these stalls by providing structured interventions that made resources and goals visible, rehearsed stakeholder interactions, and supported small, actionable steps. In addition to introducing the Commitment Readiness Gap, this study adds a readiness layer to the effectuation model, offering insights and practical interventions to help entrepreneurs convert reflection into commitments under uncertainty.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.105
GPT teacher head0.420
Teacher spread0.315 · 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