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Record W2019502520 · doi:10.1142/s1363919607001679

GAMES OF INNOVATION: THE ROLES OF NONPROFIT ORGANISATIONS

2007· article· en· W2019502520 on OpenAlex
Margaret Dalziel

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

VenueInternational Journal of Innovation Management · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEnablingPerspective (graphical)BusinessNonprofit organizationPublic relationsOpen innovationMarketingPolitical science

Abstract

fetched live from OpenAlex

Games of innovation involve four types of organisational players: firms, governments, universities, and nonprofit organisations. Of the four, nonprofit organisations are the least well understood. To capture the contributions of all types of organisational players, I adopt the perspective of a focal firm and consider the roles that other organisations play with respect to its ability to innovate. I introduce the roles of institutional enabler and institutional balancer, in which another organisation increases or decreases, respectively, the focal firm's ability to innovate by shaping the networks and markets in which it participates. I then develop propositions regarding the importance of the institutional enabler and balancer roles, and the roles of nonprofit organisations, in games of innovation.

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 score0.880
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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