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Record W2893721318 · doi:10.25222/larr.345

New Media and Support for Same-Sex Marriage

2018· article· en· W2893721318 on OpenAlexaff
Jordi Díez, Michelle Dion

Bibliographic record

VenueLatin American Research Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Guelph
FundersVanderbilt UniversityInter-American Development BankUnited States Agency for International Development
KeywordsThe InternetLatin AmericansDemocracyPopulationPoliticsSocial mediaPolitical scienceInternet usersDemographic economicsDemographyPsychologySociologyEconomics

Abstract

fetched live from OpenAlex

Research in advanced industrialized democracies on social attitudes toward same-sex marriage suggests that intergroup social contact and positive media coverage play an important role in promoting tolerance and support for same-sex marriage. Using AmericasBarometer survey data for eighteen countries in 2010, 2012, and 2014, this article examines the ways in which individual-level Internet use interacts with news exposure, country-level quality of democracy, Internet penetration, and their association with support for same-sex marriage. The results suggest that not only is Internet use associated with greater support for same-sex marriage, but that among those who both use the Internet and pay more attention to the news, the positive effects are amplified. In addition, national level of democracy, economic development, and Internet use are also associated with overall higher probabilities of supporting same-sex marriage. We find that Internet use has a strong positive association with the probability of supporting same-sex marriage as the percentage of the national population on the Internet increases. These findings extend our understanding of social and political tolerance of same-sex marriage in Latin America.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.219
GPT teacher head0.506
Teacher spread0.287 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations19
Published2018
Admission routes1
Has abstractyes

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