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Facilitating Innovation and Entrepreneurial Opportunities for Societal Challenges

2025· article· en· W4416005672 on OpenAlexaff
Amalya L. Oliver, Rotem Rittblat, Michael Lounsbury, Elke Schuessler, Timothy R. Hannigan, Donald S. Siegel

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsUniversity of OttawaUniversity of Alberta
Fundersnot available
KeywordsSocial innovationResponsible Research and InnovationGrand ChallengesGlobal challengesIntersection (aeronautics)Entrepreneurship

Abstract

fetched live from OpenAlex

This symposium explores the intersection of entrepreneurship, innovation, and societal challenges through the lens of innovation platforms. These platforms, defined as institutional structures fostering collaboration and knowledge creation, provide a unique framework for addressing global challenges such as health, sustainability, and climate change. By convening scholars from diverse research interests, this symposium examines the role of innovation platforms in enhancing entrepreneurial activities, fostering interdisciplinary research, and advancing new approaches to complex societal issues. Through four presentations, the symposium highlights diverse perspectives: how scientific paradigms influence innovation in addressing antimicrobial resistance; strategies for uniting siloed ecosystems into cross-sectoral networks; the

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0090.011
Scholarly communication0.0180.016
Open science0.0010.025
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0140.002

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 head0.081
GPT teacher head0.282
Teacher spread0.201 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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