An International Pilot Study of Volunteer Stream Monitoring Groups: The Role of Place Attachment in Volunteer Motivations
Bibliographic record
Abstract
Engaging the public in scientific research through volunteer monitoring (a form of community science) has potential to expand knowledge of conditions and to improve collaborative decision-making. Many studies have sought to understand motivations for participation and potential resulting actions or behaviors that benefit the environment. Place-based connections have been demonstrated to lead people to adopt environmentally responsible behaviors. However, few studies have considered possible differences in motivations across countries or the role place attachment may play as a driver of initial or sustained participation. The aim of this research was to determine the extent to which place attachment influences people’s decision to volunteer for stream-based water monitoring programs in three countries: the United States, Canada, and New Zealand. This pilot study applied a mixed-method approach to assess and compare motivations of volunteers via an online survey of 101 individuals and follow-up semi-structured interviews with a subset of survey participants (n = 25). Findings revealed place attachment is a motive for volunteers to participate in stream monitoring, along with concern for water resources, learning/engagement, and direct involvement in science. A statistically significant relationship (p < .05) was found between gender and motivation categories of place attachment and direct involvement in science. Some experienced volunteers indicated participation in monitoring over time enhanced their attachment to place. These findings suggest that programs seeking to gain and sustain volunteers and to create a more environmentally engaged community might focus outreach on identifying potential volunteers with existing person-place bonds and nurturing connections to place with existing volunteers.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".