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Ineffectual Orders: Habituated Effectuation in a Scaling Social Enterprise

2020· article· en· W3045836780 on OpenAlexaff
Bruce Martin, Lucia Walsh, Andrew Keating, Susi Geiger

Bibliographic record

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsCausationEntrepreneurshipSocial enterprisePositive economicsCognitionEpistemologyProcess (computing)EthnographySociologyPsychologyEconomicsPolitical sciencePublic relationsComputer science

Abstract

fetched live from OpenAlex

The institutional complexity and economics of worth literature are largely silent on the potential for conflict between particular orders of worth—meta-cognitive conventions for making and justifying decisions—to become intractable. The entrepreneurship literature is largely silent on the potential for effectuation—a meta-cognitive process informing decision-making under uncertainty—to become habituated. Our ethnographic study of a globally scaling, inclusivity social enterprise brings together these disparate literatures to show that effectuation and its alternative, causation, can act as catalysts for conflict among orders of worth, and when habituated among focal actors, hold the potential to turn a globally scaling social enterprise into a failed organization. Insights for theory and practice in hybrid organizations and entrepreneurship are provided.

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)0.005
metaresearch head score (Gemma)0.014
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.022
Scholarly communication0.0050.006
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.248
Teacher spread0.223 · 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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