Hope and optimism gaps among sexual and gender minorities of Canada
Bibliographic record
Abstract
Purpose Quantitative evidence on how sexual and gender minorities (SGMs) stand with respect to hope and optimism compared with their cisgender heterosexual peers is sparse. However, as hope and optimism are shaped by past experiences, and the SGM people generally have less advantageous lived experiences, less-favorable hope and optimism outcomes among them are very likely. The present study examines this question. Design/methodology/approach The data comprise a recently collected original dataset on the SGMs (N = 1,189) and the Canadian General Social Survey of 2016. The methodology is multivariate regression, also incorporating various sensitivity tests. To mitigate the lack of randomization in the SGM Survey benchmarking factors are used. Findings At constant levels of current socioeconomic attainment, the SGMs are found to be markedly less hopeful than cisgender heterosexual women and men. Large gaps are also found in sexual/gender identity regarding optimism about future life and future financial state. For the optimism outcomes, the SGM gaps are somewhat larger with cisgender heterosexual men than with cisgender heterosexual women. These gaps are dampened by the degree of SGM identity disclosure, especially by outness to the family members. Within the SGM groups, the similarity hypothesis finds greater support than the alternative. Although evidence emerges that trans men likely fare non-negligibly worse than other SGMs in the hopefulness metric. Originality/value Using an original dataset, this study reports critical deficits in hope and optimism among the Canadian SGMs, and adds to the growing literature showcasing the role of hope and optimism as policy tools in poverty reduction and inclusion promotion.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".