Impact Assessment, Sustainability, and Climate Change: Lessons from Lower Churchill
Bibliographic record
Abstract
The attainment of sustainability is the overarching objective of impact assessment (IA). Over the years, IA has evolved from being a predominantly biophysical- environment assessment venture to a multicentric undertaking including hundreds of IA modes. IA’s proliferation has been attributed to the inadequacy of previously dominant modes (e.g. Environmental Impact Assessment and Social Impact Assessment) to cater to other areas of humanity’s concerns or recent phenomena. Climate change is one of such phenomena and the conceptualization of climate change impact assessment has been the response of the IA movement. Drawing lessons from the Lower Churchill project in Newfoundland and Labrador (Canada), this paper argues that a climate change centric IA risks overlooking, triggering or exacerbating other sustainability challenges. This possibility is even more acute in projects misconstrued as sustainable given their low emission characteristic. An integrated approach to IA with sustainability as the organizing principle is proposed as key to preventing climate change from becoming another frontier of unsustainability.\nLa coopération transnationale en matière d’information fiscale a pour rôle crucial de donner aux administrations fiscales les moyens de percevoir les recettes fiscales dans leur intégralité et en temps voulu, réduisant ainsi le fossé créé par la fraude et l’évasion fiscales à l’échelle internationale. Cependant, l’adéquation des systèmes d’échange d’informations fiscales transnationaux établis pour lutter contre la fraude et l’évasion fiscales internationales a été sévèrement critiquée et une nouvelle vague de progrès en matière de transparence a débuté après la crise économique mondiale de 2008. Dans cette optique, la Turquie a fait de la transparence fiscale transfrontalière une priorité de son programme politique. Cependant, la Turquie a mis en œuvre très lentement les nouveaux accords de coopération fiscale transnationale. En outre, l’approche de la Turquie en matière d’échange d’informations présente d’importantes lacunes. Dans le présent article, nous démontrons les raisons du manque d’urgence du gouvernement turc à rendre ses affaires fiscales transfrontalières plus transparentes. Nous montrons comment la transparence fiscale transfrontalière pourrait être inscrite à l’agenda politique turc. L’article conclut que la mise en œuvre universelle, rapide et cohérente d’une réponse coordonnée à la fraude et à l’évasion fiscales transfrontalières par des efforts de transparence est liée au soutien de l’opinion publique nationale et ne peut donc être obtenue par le gouvernement qu’en tandem avec un mandat populaire.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".