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Record W2782003139 · doi:10.24124/c677/20171419

Canadian Arab Youth Vote 2015

2018· article· en· W2782003139 on OpenAlexaffvenueabout
Melissa Finn, Bessma Momani

Bibliographic record

VenueCanadian Political Science Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsCentre for International Governance InnovationBalsillie School of International AffairsUniversity of Waterloo
Fundersnot available
KeywordsMainstreamPoliticsVotingPolitical scienceApathyGeneral electionNorm (philosophy)Presidential electionPolitical economySociologyLawPsychology

Abstract

fetched live from OpenAlex

In this paper, we seek to unpack some of the nuances about what motivated Canadian Arab youth to vote in the 2015 election and how their decisions inform the wider literature. How does the voting behaviour of Canadian Arab youth during the 2015 election support or challenge mainstream academic theories about ethno-cultural youth political decision-making and voting preferences? What concepts might help us better understand this rising demographic, its political animus, and its significance for Canadian politics? Of great interest in this paper is the investigation into whether voter apathy historically reported for young people and ethno-cultural communities continued to hold in the 2015 election. This paper critically interrogates what the 2015 federal election meant to Canadian Arab youth. We identify the predominant political inclinations of and issues for young Arab Canadians through the findings of structured focus groups. Our findings indicate that Arab Canadian youth were highly engaged with the issues of the election and apathy was the exception rather than the norm. Canadian Arab youth’s ethno-cultural background does explain their voting behaviour during the 2015 election, but bread and butter issues are also a concern for many young people.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.007
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.030
GPT teacher head0.311
Teacher spread0.280 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2018
Admission routes3
Has abstractyes

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