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Record W2562716445

The drive to innovation: The privileging of science and technology knowledge production in Canada

2012· dissertation· en· W2562716445 on OpenAlexaboutno aff
Laura Cauchi

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge productionProduction (economics)EngineeringPolitical scienceBusinessKnowledge managementComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This dissertation project explored the privileging of knowledge production in science and technology as a Canadian national economic, political and social strategy. The project incorporated the relationship between nation-state knowledge production and how that knowledge is then systematically evaluated, prioritized and validated by systems of health technology assessment (HTA). The entry point into the analysis and this dissertation project was the Scientific Research and Experimental Design (SR&ED) federal tax incentive program as the cornerstone of science and technology knowledge production in Canada. The method of inquiry and analysis examined the submission documents submitted by key stakeholders across the country, representing public, private and academic standpoints, during the public consultation process conducted from 2007 to 2008 and how each of these standpoints is hooked into the public policy interests and institutional structures that produce knowledge in science and technology. Key public meetings, including the public information sessions facilitated by the Canada Revenue Agency and private industry conferences, provided context and guidance regarding the current pervasive public and policy interests that direct and drive the policy debates. Finally, the “Innovation Canada: A Call to Action Review of Federal Support to Research and Development: Expert Panel Report,” commonly referred to as “The Jenkins Report” (Jenkins et al., 2011), was critically evaluated as the expected predictor of future public policy changes associated with the SR&ED program and the future implications for the production of knowledge in science and technology. The method of inquiry and analytical lens was a materialist approach that drew on the inspiring frameworks of such scholars as Dorothy Smith, Michel Foucault, Kaushik Sunder Rajan, Melinda Cooper, and, Gilles Deleuze. Ultimately, I strove to illuminate the normalizing force and power of knowledge production in science and technology, and the disciplines and structures that encompass it and are hooked into it where the privileging of such knowledge becomes hegemonic within and by the regimes of knowledge production that created them.

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 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)0.010
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.015
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.070
GPT teacher head0.448
Teacher spread0.378 · 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 teacher head, not a consensus.

Study designOther design
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
Published2012
Admission routes1
Has abstractyes

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