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Record W2946787014 · doi:10.1093/ser/mwz014

Social entrepreneurship as field encroachment: how a neoliberal social movement constructed a new field

2019· article· en· W2946787014 on OpenAlexaff
Jason S. Spicer, Tamara Kay, Marshall Ganz

Bibliographic record

VenueSocio-Economic Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial entrepreneurshipField (mathematics)LegitimacySocial movementSocial orderPoliticsEntrepreneurshipSociologyPolitical economyResource mobilizationEconomic systemPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract In explaining the emergence of new strategic action fields, in which social movements’ and organizations’ logic, rules and strategies are forged, inter-field dynamics remain under-explored. The case of Social Enterprise and Entrepreneurship (SEE) shows how new fields can emerge through field encroachment, whereby shifts among overlapping fields create structural opportunities for the ascendency of new fields, which may adapt logics borrowed from adjacent fields to construct legitimacy. SEE leveraged the 1980s’ shift between first-order market and state fields to encroach on the political strategies of community organizing, birthing a neoliberal social movement to create a new field addressing social problems using market-based, profit-motivated approaches. With its borrowed veneer of justice, SEE rapidly developed a high academic and public profile over just three decades, despite little evidence its approach to solving social problems works. In encroaching on proven political strategies for solving social problems, it may further undermine democratic practices.

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)0.012
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.055
Scholarly communication0.0120.009
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.260
Teacher spread0.240 · 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

Citations60
Published2019
Admission routes1
Has abstractyes

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