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Innovation Potentiality: Measuring Organisational Innovation Potential in the Canadian Public Sector

2020· article· en· W3045708691 on OpenAlex
Jo’Anne Langham, Neil Paulsen

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCommitStatus quoBusinessPublic sectorPoliticsPublic relationsKnowledge managementMarketingPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Establishing a design and innovation (D&I) capability within a public sector organisation takes serious commitment and sponsorship from senior management. The leadership must commit to structural, political and cultural changes for the capability to succeed. When effective, design and innovation may cause disruption in current operational practices; become a catalyst for change; and challenge the powerful status quo. Such purposeful disruption can lead to significant progress and advancement for the organisation. However, these capabilities can often flounder due to insufficient preparation and lack of genuine dedication and endurance to overcome the obstacles that are inevitably encountered. This paper proposes a measurement model to evaluate the organisational readiness for D&I in public sector organisations. It is tested using the department of Innovation, Science and Economic Development (ISED) in Canada. The final score of 61.38% as the organisation’s innovation potential shows an organisation wanting to innovate but struggling with the appropriate implementation mechanisms and cultural norms. Through understanding the strength of factors contributing to the incorporation, practice and management of D&I, organisations can increase the probability of success and growth of these capabilities. Practical implications for organisational structures and operating models related to D&I are discussed.

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)0.001
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: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.010
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.227
GPT teacher head0.333
Teacher spread0.106 · 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