Volunteering on Nature Conservation Projects: Volunteer Experience, Attitudes and Values
Bibliographic record
Abstract
In many countries volunteers are playing an increasing role in nature conservation. Many factors have lead to this trend including reduced government budgets assigned for conservation and an increased awareness and interest expressed by each country's general population to contribute to environmental health and nature conservation. This paper utilizes descriptions of volunteers' experiences participating in Volunteer for Nature, a volunteer programme operated by Canadian conservation NGOs, which facilitates the participation of Ontario-Residents' in 3 to 17-day working vacations involving habitat restoration and recreation infrastructure projects located in natural environments. This paper describes volunteer attitudes and values regarding nature, as highlighted through the description of their volunteering experiences and their characterization and perceptions of nature. Using a constructivist approach to data collection and analysis, the researchers found that volunteers conceptualized nature in four different ways: ‘nature in crisis,’ ‘nature as it should be,’ ‘nature as outside or something different,’ and ‘nature as nurturing.’ Volunteers' egoistic concerns centred on the self (e.g., my health, my favourite activity, my grandchildren), altruistic concerns centred on other people (society in general, people in my community) and biocentric or ecocentric concerns, centred on living things (e.g., plants, ecosystems, birds, the environment in general). While biocentric concerns were cited as important, they were not ascribed greater value than the egoistic or altruists concerns. The volunteer tourism experience generally failed to change the volunteers' perceptions of nature from an ‘external’ phenomenon to an ‘internal’ one, (i.e., changing treatment of nature as ‘other’ to a more ecocentric approach, which incorporates nature into ‘self’). Implications for generating a pro-environmental attitudes and behaviours amongst citizens are discussed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".