Monogamy in question: Predictors of perceived shifts in attitudes toward monogamy and consensual non-monogamy during the COVID-19 pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has been linked to increased self-reflection and shifts in personal priorities, including romantic and sexual relationships. Drawing on socioemotional selectivity theory and terror management theory, this study examines whether the pandemic influenced U.S. adults’ attitudes toward monogamy and openness to consensual non-monogamy (CNM). Using a national sample of 2,004 adults surveyed in January 2021, the authors explored the participants’ perceived changes in the importance of monogamy and the likelihood of pursuing CNM relationships, along with demographic correlates. The results showed that for most participants, monogamy’s importance to them remained stable, yet 23% reported decreased importance, and 11% expressed greater interest in CNM relationships. Demographic factors, such as age, transgender identity, sexual orientation, and parental status, were significantly associated with attitudes toward monogamy and CNM. These findings highlight the pandemic’s dual role in reinforcing monogamy for some while prompting others to explore alternative relationship structures. This study underscores the importance of understanding relational shifts during societal disruptions and offers a foundation for future research on how crises shape intimate relationships.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".