Place-Based Stewardship Education: Nurturing Aspirations to Protect the Rural Commons
Bibliographic record
Abstract
In this mixed-methods study, we examine the potential of place-based stewardship education (PBSE) for nurturing rural students’ community attachment and aspirations to contribute to the preservation of the environmental “commons.” Analyzing pre- and post-experience surveys (n = 240) and open-ended responses (n = 275) collected from middle school students in a Northeast Michigan school district, we found significant increases in students’ environmental sensitivity, environmentally responsible behaviors, community attachment, and confidence in their capacities for civic action. Analyses of open-ended responses pointed to the potential of PBSE to nurture students’ identification with their community and to increase their commitment to stewardship of their community's natural resources. This study makes a unique contribution to the literature on rural schools by focusing on the environmental commons and younger generations’ commitments to preserve it as an asset of rural communities. By linking students’ learning with collective action to preserve the environmental commons, PBSE can expand students’ aspirations for the kind of world they want to live in and the roles they might play in it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".