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Record W2038770361 · doi:10.1177/1363460708096912

Legal Struggles and Political Resistance: Same-Sex Marriage in Canada and the USA

2008· article· en· W2038770361 on OpenAlexafffundabout
Nancy Nicol, Miriam Smith

Bibliographic record

VenueSexualities · 2008
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInjusticePoliticsResistance (ecology)Legal consciousnessSociologyPower (physics)LawGender studiesPolitical science

Abstract

fetched live from OpenAlex

This article explores the nature of legal struggles surrounding same-sex marriage in the USA and Canada, focusing specifically on the ways in which the cultural power of law is used to frame claims of injustice and to develop strategies of political resistance. Drawing on theoretical perspectives from the literatures on 'law and social movements' and 'legal consciousness', the article compares the claims-making discourse and strategies of same-sex couples seeking access to legal civil marriage in the USA and Canada. Based in part on interviews with same-sex couples, lawyers and political activists, the article demonstrates the ways in which the claims of law have been used to frame political strategies in places where same-sex marriage is 'illegal', the ways in which claims of legal equality are enacted, produced and explained by same-sex couples, and the ways in which equality discourse is deployed as a strategic political resource in the struggle over same-sex marriage.

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 score0.090
Threshold uncertainty score0.656

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0400.014
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.323
Teacher spread0.289 · 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

Citations23
Published2008
Admission routes3
Has abstractyes

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