Land, Sea, and Us: Planning for Climate Change on The Rock
Bibliographic record
Abstract
This paper discusses the impact that climate change will have on Newfoundlanders and their relationship to the land and sea around them, specifically within the Avalon Peninsula (the most eastern section of the island). As an island, Newfoundland will have different climate change concerns than many parts of mainland Canada. I approach these questions of identity, relationship, and climate change through analyzing the relationship Newfoundlanders have to the island by way of ethnographic interviews and a review of literature pertaining to the people and cultures in Newfoundland. Cultural landscape theory is employed to contextualize and understand how Newfoundlanders situate themselves in Newfoundland and relate to the landscape. The impacts of climate change are understood from both the scientific literature on the physical changes associated with climate change, and how these changes will impact the relationship between Newfoundlanders and the island. I employ political ecology to understand the environmental politics at play in Newfoundland in regards to climate change planning at the provincial level. In this paper, I find that climate change planning in Newfoundland is lacking, that change is anticipated but felt to be far off, and that the province of Newfoundland and Labrador’s connection to the oil and gas sector hinders the province’s ability to properly plan for 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".