Gender Differences in Pro‐Environmental Intentions: A Cross‐National Perspective on the Influence of Self‐Enhancement Values and Views on Technology*
Bibliographic record
Abstract
While many studies have addressed the complex relationship between gender and environmental constructs, few have attempted to determine just how gender influences environmentalism. We argue that the interaction of gender with other sociocultural variables must be examined. Our study includes two of these variables: technological values and self‐enhancement values. Study results indicate that the effect of gender on environmental intentions is moderated by these two variables. This is established in a multicountry study of college students in the United States, Canada, and Germany. In examining willingness to change consumption behaviors, when controlling for self‐enhancement or technological values, the gender effect holds only when there are high scores for the other variable. When technological or self‐enhancement scores are low, men and women are equally willing to change their intentions. The gender by technology effect was moderated somewhat by country. Thus, gender alone does not function independently in its impact on respondents’ willingness to change consumption behaviors. The study results have implications for future research on the relationship between gender and environmentalism and for environmental education efforts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".