Young Canadians and Climate Change: Vulnerability, Adaptive Capacity, Education, and Agency
Bibliographic record
Abstract
Canada’s climate is warming at twice the global rate and its population is already experiencing several adverse effects of climate change. Canadian children and youth are among the most vulnerable to climatic changes due to physiological and developmental factors, yet their vulnerability, adaptation, and adaptive capacity are largely undocumented in the climate change literature. Several factors, including health, socioeconomic, and sociocultural factors, contribute to the vulnerability of Canadian children and youth to climate change. Although health factors of vulnerability and the health impacts of climate change on these groups have been documented in the published and grey literatures to a certain extent, information on the socioeconomic and sociocultural factors contributing to their vulnerability remains scarce. As a signatory to the Paris Agreement and the Convention on the Rights of the Child, Canada has binding obligations to reduce its carbon emissions, plan and implement adaptation measures for its citizens, including children and youth, and to provide the latter with a healthy environment in which to grow up. Although children and youth have contributed very little to anthropogenic climate change and are not decision-makers in policy processes, they are disproportionately affected by the climate inaction of previous generations because their lives will be increasingly impacted. Furthermore, young people worldwide, including marginalized children and youth (e.g., those who live in poverty and/or are Indigenous, racialized, immigrants, disabled, etc.) were largely excluded from consideration as a group in global climate change mitigation and adaptation decision-making processes until their groundswell of activist leadership, beginning in 2018. Despite, or perhaps in response to this marginalization, young people across Canada are taking a stand against climate inaction and playing leadership roles in climate action activism in this country. Their perceptions, experiences, and contributions, however, remain noticeably and regrettably scarce in the published climate change literature. This paper discusses implications for education, research, and policy.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.027 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".