What Drives Climate Action in Canada’s Provincial North? Exploring the Role of Connectedness to Nature, Climate Worry, and Talking with Friends and Family
Bibliographic record
Abstract
Despite widespread calls to action from the scientific community and beyond, a concerning climate action gap exists. This paper aims to enhance our understanding of the role of connectedness to nature in promoting individual-level climate action in a unique setting where climate research and action are lacking: Canada’s Provincial North. To begin to understand possible pathways, we also examined whether climate worry and talking about climate change with family and friends mediate the relationship between connectedness to nature and climate action. We used data collected via postal surveys in two Provincial North communities, Thunder Bay (Ontario), and Prince George (British Columbia) (n = 628). Results show that connectedness to nature has a direct positive association with individual-level climate action, controlling for gender and education. Results of parallel mediation analyses further show that connectedness to nature is indirectly associated with individual-level climate action, mediated by both climate worry and talking about climate change with family and friends. Finally, results suggest that climate worry and talking about climate change with family and friends serially mediate the relationship between connectedness to nature and with individual-level climate action. These findings are relevant for climate change engagement and action, especially across Canada’s Provincial North, but also in similar settings characterized by marginalization, heightened vulnerability to climate change, urban islands within vast rural and remote landscapes, and economies and social identities tied to resource extraction. Drawing on these findings, we argue that cultivating stronger connections with nature in the places where people live, learn, work, and play is an important and currently underutilized leverage point for promoting individual-level climate action. This study therefore adds to the current and increasingly relevant calls for (re-)connecting with nature that have been made by others across a range of disciplinary and sectoral divides.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".