MétaCan
Menu
Back to cohort
Record W2523213871 · doi:10.1108/ejim-01-2016-0010

Managing multiple logics in partnerships for scaling social innovation

2016· article· en· W2523213871 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

VenueEuropean Journal of Innovation Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsCentralitySocial innovationOriginalityKnowledge managementInnovation managementSociologyBusinessComputer sciencePublic relationsPolitical scienceSocial scienceMathematicsQualitative research

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to contribute to the field of social innovation by examining institutional logics at the level of inter- and intra-organizational partnerships for scaling impact. Design/methodology/approach The authors use a set of case studies from the Stanford Social Innovation Review to analyze success in scaling social innovations applying the logic compatibility-centrality matrix proposed by Besharov and Smith (2014), which aims to reveal the potential for conflict in organizations based on the diversity of logics present and the degree to which they are compatible with each other. Findings The findings shed insight on how individuals and organizations are able to manage logic multiplicity in the context of partnerships for scaling social innovation. Originality/value The authors build on recent work that recognizes logic multiplicity in social enterprises resulting from their hybrid nature, and the authors add to the existing debate by introducing to the discussion contributions from cognitive theory that help explain why organizational cultures evolve and scale out the way they do.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.258
Teacher spread0.174 · 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