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Record W2611642597

The Religious Right and the Battle Over Sex Education in the United States

2017· article· en· W2611642597 on OpenAlexaff
Desmond A. D. O'Doherty

Bibliographic record

VenueSymposia: The Journal of Religion · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsYork University
Fundersnot available
KeywordsImmoralityIdeologyChristian rightGender studiesCurriculumLesbianSociologyHuman sexualityQueerHeteronormativityPolitical scienceTransgenderLegislationReligious educationPublic opinionPoliticsLawMorality
DOInot available

Abstract

fetched live from OpenAlex

Sexuality has a way of inciting polarized debates and dividing public opinion. The Religious Right has been successful in influencing elections and legislation, which has helped them obtain the funding necessary to regulating sex education curricula in the United States. Sex education programs in the United States have been profoundly influenced by certain conservative Christian ideologies that are in support of a heteronormative agenda. Through observing how the Religious Right became involved with sexuality politics and how certain conservative Christians sought to control sex education in the United States, it becomes possible to identify the conservative Christian influence on sex education curricula. This project claims that religion has been utilized as a political tool by certain Christian groups for the purpose of combating supposed sexual immorality in the United States. This conservative Christian ideology has had an immense influence on its sex education curricula resulting in the promotion of a particular kind of heteronormativity that has affected the lesbian, gay, bisexual, transgender and queer (LGBTQ+) community. Determining the future of sex education in the United States is no easy task, however, through educating American citizens about alternate versions of sex education curricula it is possible to combat the Religious Rights religious and heteronormative ideologies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.301
Teacher spread0.295 · 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
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
Published2017
Admission routes1
Has abstractyes

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