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Record W4230904475 · doi:10.22215/etd/2016-11279

Changing Course: Commercializing Canadian Airport, Port and Rail Governance- 1975 to 2000

2016· dissertation· en· W4230904475 on OpenAlexaffabout
Mark Davis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCommercializationGovernment (linguistics)Corporate governancePort (circuit theory)IdeologyPublic policyBusinessEconomic policyPublic administrationPolitical scienceEconomyEconomic growthEconomicsFinancePoliticsEngineeringMarketing

Abstract

fetched live from OpenAlex

This thesis examines the historical public policy circumstances surrounding the Government of Canada’s decision to commercialize Canadian National (CN) Railways, as well as federal airports and ports over the period 1975 to 2000. Its focus is on testing one specific empirical hypothesis: That the commercialization of federal airport and port assets between 1975 and 2000 occurred primarily due to: (i) federal government concerns over the growing size of the national debt and deficit; and (ii) the emergence of the neoliberal ideology in Canada and its growing influence throughout federal policy making, as witnessed by the swift 1995 privatization of CN Railways.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.885

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0040.004
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.218
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2016
Admission routes2
Has abstractyes

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