Environmental Philanthropy and Environmental Behavior in Five Countries: Is There Convergence Among Youth?
Bibliographic record
Abstract
Abstract This paper compares and contrasts environmental philanthropy, environmental behavior, and their determinants among university students in five countries: Canada, Germany, Israel, South Korea, and the United States. The paper’s unique contribution to the nonprofit literature is its focus on environmental philanthropy as an unexplored form of philanthropic behavior, and the ability to test environmental philanthropy in an international setting and in comparison to other modes of environmental behavior. By environmental philanthropy, we mean giving to, and volunteering in, various environmental non-governmental organizations, and by environmental behavior, we refer to daily behaviors in the private sphere with ecological implications. We hypothesize that although the five countries vary on several characteristics, the student populations—who are young, educated, and exposed to global ideas and norms—will be relatively similar to each other in their environmental and philanthropic behavior and in the determinants of such behavior. To test this hypothesis, a standardized questionnaire was administered to 8,477 students on five campuses. Results show significant differences between students in their environmental philanthropic behavior, as well as in the demographic and attitudinal determinants of such behaviors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".