The Age of Toxicity: The Influence of Gender Roles and Toxic Masculinity in Harmful Heterosexual Relationship Behaviours
Bibliographic record
Abstract
Although heterosexual relationships have been evolving since the dawn of humanity, there continues to be a considerable amount of inequality, toxicity, and dissatisfaction within heterosexual couplings. This paper explores the ways in which socially prescribed gender roles and toxic masculinity contribute to behaviours which lead to toxicity and unhappiness in heterosexual relationships. The behaviours that this paper will discuss include coercive control as well as physical and sexual violence, all of which are behaviours that according to current literature, are shockingly common in heterosexual relationships. Moreover, the present paper will investigate previous literature in order to explore these concepts in depth through theoretical concepts as well as previous qualitative and quantitative studies done on heterosexual relationship satisfaction. This particular research paper aims to identify and define the concepts of socially prescribed gender roles and toxic masculinity, before applying these concepts to the previously mentioned relationship behaviours in order to determine just how these social concepts contribute to or cause these behaviours in heterosexual couplings.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".