The Religious Right and the Battle Over Sex Education in the United States
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".