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Record W1566380626

Incrementalism, Civil Unions, and the Possibility of Predicting Legal Recognition of Same-Sex Marriage

2010· article· en· W1566380626 on OpenAlexaff
Erez Aloni

Bibliographic record

VenueDuke journal of gender law & policy · 2010
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIncrementalismLegalizationLesbianPoliticsVariety (cybernetics)Political scienceState (computer science)Same sexLawSociologyGender studies
DOInot available

Abstract

fetched live from OpenAlex

Scholars who have examined the legal recognition of same-sex partnerships in European countries have concluded that the path to the legalization of same-sex marriage follows an incremental process involving specific stages. They suggest that it is possible to predict, based on certain visible social and legal processes or assessable parameters, which U.S. states will be the next to recognize same-sex marriage. These scholars argue that such small cumulative legal changes at the state level constitute the best means of legalizing same-sex marriage in the United States, and that civil unions are a necessary step in this process. This article shows that predictions based on these theories have not been accurate and that attempts to generalize the experience of legalizing same-sex marriage overlook a variety of often significant and sometimes subtle social, political, and legal differences between the United States and Europe. Therefore, these theories cannot sufficiently explain how social change happens and cannot be used to formulate strategic plans for legalizing same-sex marriage in the United States. This article also proposes that the adoption of civil unions can significantly delay legal acceptance of same-sex marriage. It suggests that the theories overlooked the fact that in some European countries, lesbian and gay organizations were more interested in securing partnership rights for same-sex couples, rather than marriage itself. This path is the one that advocates in the United States should take.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.199
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.322
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 teacher head, 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

Citations9
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDuke journal of gender law & policySame topicReproductive Health and TechnologiesFrench-language works237,207