The Consequences of Unfreedom: Learning from Story Amidst a Global Climate Crisis
Bibliographic record
Abstract
As the world navigates the impending consequences of climate change, Canada remains one of the few countries to reject the right to a healthy environment for its citizens within the Canadian Constitution. Although Canada purports itself to be a free and democratic society, many argue that their freedoms are continually neglected by laws that continue to disregard the environment and, therefore, their right to a healthy existence. This article is an investigation into a particular word that is woven throughout Canada’s Constitution: “freedom.” It is an investigation into the conflicting understandings of the word and how these contrasting meanings have impacted Canada’s Constitution and its relationship to land. This article analyzes the history of freedom as seen through a liberal belief system and contrasts this understanding with Indigenous concepts of freedom, as told through Haisla and Nuu-chah-nulth stories. These narratives explore how the differing concepts of freedom have affected relationships with the land and the laws that govern the land. Finally, the discussion of these themes draws upon the possibility of using story within Canada’s laws to change the Constitution’s current relationship with the land in order to mitigate the potential effects of climate change. I argue that the liberal, colonialist world view is ever present in our current legal system and is in fact facilitated through the word “freedom.” Until we begin to re-story our Constitution through a diversity of understandings and world views, Canada will continue to ignore the looming ramifications of climate change.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.042 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.008 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".