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Record W3010655802

Provincial Involvement in Canadian Immigration Policy Making: The Case of Ontario

2013· dissertation· en· W3010655802 on OpenAlexaboutno aff
Olga Georgievová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationImmigration policyPolitical sciencePublic administrationPolicy makingLaw
DOInot available

Abstract

fetched live from OpenAlex

Asymmetry and executive federalism are two unique features that dominate the Canadian political landscape. As a result, federal and provincial governments are in direct negotiations over many current public policy issues, immigration policy notwithstanding. In order to understand the current immigration debate and to evaluate the benefits of greater provincial involvement, it is first necessary to comprehend what motivates provinces to be active in immigration policy-making. Ontario presents an interesting example of a province that used to be quite content with leaving the federal government dominant in the immigration arena but that has recently changed its attitude completely: Ontario is now much more assertive in presenting its demands. Through a comprehensive literature review and a series of interviews of key immigration policy figures, this study analyzes the main motives of Ontario with respect to immigration policy. It finds that they were primarily of economic, demographic, and political nature and that they were mainly connected to the relative decline of Ontario's position within Canada.

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)0.004
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.850

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0470.008
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0030.003
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 head0.008
GPT teacher head0.264
Teacher spread0.256 · 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
Published2013
Admission routes1
Has abstractyes

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