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Record W4384196489 · doi:10.1515/9780773596535

Asleep at the Switch

2014· book· en· W4384196489 on OpenAlexaboutno aff
Bruce Smardon

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2014
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Since 1960, Canadian industry has lagged behind other advanced capitalist economies in its level of commitment to research and development. Asleep at the Switch explains the reasons for this underperformance, despite a series of federal measures to spur technological innovation in Canada. Bruce Smardon argues that the underlying issue in Canada's longstanding failure to innovate is structural, and can be traced to the rapid diffusion of American Fordist practices into the manufacturing sector of the early twentieth century. Under the influence of Fordism, Canadian industry came to depend heavily on outside sources of new technology, particularly from the United States. Though this initially brought in substantial foreign capital and led to rapid economic development, the resulting branch-plant industrial structure led to the prioritization of business interests over transformative and innovative industrial strategies. This situation was exacerbated in the early 1960s by the Glassco framework, which assumed that the best way for the federal state to foster domestic technological capacity was to fund private sector research and collaborative strategies with private capital. Remarkably, and with few results, federal programs and measures continued to emphasize a market-oriented approach. Asleep at the Switch details the ongoing attempts by the federal government to increase the level of innovation in Canadian industry, but shows why these efforts have failed to alter the pattern of technological dependency.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2014
Admission routes1
Has abstractyes

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