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Record W2791322463 · doi:10.1111/ssqu.12496

Courts and Issue Attention in Canada

2018· article· en· W2791322463 on OpenAlexaboutno aff
Nicholas D. Conway, Soren Jordan, Joseph Daniel Ura

Bibliographic record

VenueSocial Science Quarterly · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperHomosexualityNormativePublicationDemocracyGay rightsPolitical scienceSociologyLawPolitics

Abstract

fetched live from OpenAlex

Objective To inform international discourse about judicial countermajoritarianism, we assess whether decisions enhancing gay rights by Canadian courts increase the media's attention to homosexuality and related topics. Method We first collect a data set of monthly counts of relevant articles published in two prominent Canadian newspapers and then estimate Markov‐switching models to evaluate whether increases in media attention to homosexuality are coincident with judicial decisions enhancing gay rights in Canada. Results Each of five landmark gay rights decisions is coincident with a period of heightened media attention to homosexuality. The data show that Canadian newspapers publish nearly twice as many relevant stories during these “active” regimes compared to “inactive” periods. Conclusion Canadian courts can increase attention to issues in the national media. This result supports a dynamic view of the interaction between courts and democratic majorities in place of the static view of democracy endemic to normative discourse about judicial countermajoritarianism.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.715

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.011
Science and technology studies0.0070.003
Scholarly communication0.0070.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.285
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 designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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