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Record W2100512287 · doi:10.1123/jsm.26.3.213

Determinants of an Innovation Process: A Case Study of Technological Innovation in a Community Sport Organization

2012· article· en· W2100512287 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

VenueJournal of Sport Management · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsProcess (computing)Innovation processBusinessMarketingInnovation managementKnowledge managementKey (lock)Work in processComputer science

Abstract

fetched live from OpenAlex

There has been little attention given to examining innovation under the conditions in which community sport organizations (CSO) operate. In this case study, the process under which one CSO undertook a technological innovation is explored. The purpose of this research was to classify the determinants that contributed to the innovation process, and identify at which particular stages of innovation those determinants were critical. Interviews and focus groups with key stakeholders were conducted during the innovation process. Observations were made at important points during the implementation of the innovation. Leadership commitment, pro-innovation characteristics, organizational capacity, simple organizational design, and involved and interested external parties were identified as determinants of this technological innovation. The findings illustrate multiple determinants of innovation at the managerial, organization, and environmental levels. Some of these span the entire innovation process, while others are critical only at particular stages.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.044
GPT teacher head0.358
Teacher spread0.315 · 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