What Makes an Environmental Steward? An Individual Differences Approach
Bibliographic record
Abstract
Engaging in environmental stewardship is critical for sustainability. Understanding individual differences and engagement is an important gap in present scholarship and addressing it is necessary to understand individual factors that relate to the types of activities engaged in, motivations and barriers to environmental stewardship. We surveyed 637 Canadian and American adults via Amazon Mechanical Turk, querying a range of demographic, psychological and environmental perceptions factors as well as motivations and barriers to stewardship activities. Respondents were ultimately grouped into Non-Stewards, Home-Oriented Stewards and Community-Oriented Stewards. Few differences were found among these groups. However, Home-Oriented Stewards and Community-Oriented Stewards exhibited very different initial and ongoing motivations to engage in environmental stewardship. Accordingly, we identify stewardship motivations as a potential leverage point and as one of several promising avenues for future research related to enhancing engagement in environmental stewardship for the sustainability of the planet.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".