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Record W6989477841

Behind New Eyes: The Expression of Dual Loyalties Among Young Canadians & Newcomers

2021· dissertation· en· W6989477841 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsFeelingIdentity (music)CharterAlienationConstitutionDiversity (politics)Immigration
DOInot available

Abstract

fetched live from OpenAlex

Using survey data drawn from the 2014 Provincial Diversity Project, this thesis provides a look at how the 1982 Constitution Act and the Charter of Rights and Freedoms shaped the political identities of Canadians and their understanding of the federation. More specifically, it examines how native-born Canadians and first-generation immigrants balance provincial and federal identities. My findings show that those introduced to Canada following the enactment of the 1982 Constitution have a stronger pro-Canada balancing of identity and weaker feelings of regional alienation relative to those introduced before 1982. \n \nAdditionally, this thesis explores the limits of institutional learning theory by examining how the strength of Canadian identity may predict the levels of support for national policies: multiculturalism, bilingualism, the equalization payments program, and feelings of regional alienation. My findings show that generally, the relationship between strength of Canadian identity and support for national policies is of equal strength among pre-, peri-, and post-Charter generations. Ultimately this thesis concludes that while it cannot demonstrate a clear generational break in the political behaviour of native-born Canadians and first-generation immigrants, the observed differences between Charter relative generations can be attributed to the enactment of the 1982 Constitution.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.123
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.305
Teacher spread0.274 · 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
Published2021
Admission routes1
Has abstractyes

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