The Prevalence of Stereotypes Against the LGBTQ Community and the Effect of Education on Those Stereotypes
Bibliographic record
Abstract
Stereotyping against the LGBTQ community is a major problem in modern society. Previous research has shown that stereotyping can be reduced through targeted education about the stereotyped group. This study aims to further research the effect of education on stereotypes as well as the prevalence of stereotypes against the LGBTQ community in a public high school in North Carolina. Building on existing work from Canada, this study questions the use of education in changing stereotypes and what is the baseline prevalence of those stereotypes. Based on previous peer-reviewed, published literature, this study will survey both students and teachers to establish a baseline of stereotyping occurring at this location. The researcher will teach a class about stereotypes and the LGBTQ community and measure the level of stereotypes before and after the presentation. Analysis showed that this high school had low levels of discrimination, which is a major sign of low levels of stereotyping. It also showed that education had a low-grade negative impact against stereotyping, effectively increasing stereotyping.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".