Bibliographic record
Abstract
According to Lennon-Dearing and Delavaga (2015, p. 412), “there has been a dramatic increase in anti-lesbian, gay, bisexual, and transgender legislative initiatives in Canada within the last several years. This policy brief discusses the complexities and contradictions associated with the relationship of policy, laws and same-sex intercourse. Although there is no law in Canada prohibiting same-sex intercourse, there are many legal discriminations and criminal regulations that negatively influence the lives of members of the Lesbian, Gay, Bisexual, Transgender, Queer community (LGBTQ+) and other related communities in Canada (Smith, 2020). This brief is intended to direct Canadian Parliament in altering section 159 of the Criminal Code, which states the Legal Age of Consent for anal sex is 18 years old, unless it is an act engaged in, in private, between husband and wife” (Library of Parliament, 2017; Smith, 2020). This is discriminatory towards the LGBTQ+ community because the Legal Age of Consent in Canada is 16 years old (Smith, 2020). This brief recommends removing section 159 from Canada’s Criminal Code, expungement of Criminal Records of those charged with offences related to anal intercourse, and education for policymakers on the LGBTQ+ community
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 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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".