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Record W7005047572

From Paris to Projects Clarifying the Implications of Canada’s Climate Change Mitigation Commitments for the Planning and Assessment of Projects and Strategic Undertakings (Summary Report)

2019· article· en· W7005047572 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeClimate change mitigationParliamentGlobal warmingGovernment (linguistics)Greenhouse gasBest practice
DOInot available

Abstract

fetched live from OpenAlex

By signing the Paris Agreement, Canada made a commitment to do our fair share to limit global average temperature rise to “well below 2°C” relative to pre-industrial levels, and to pursue “efforts to limit the increase to 1.5°C.” The federal Impact Assessment Act that is now before Parliament requires consideration of whether assessed undertakings would “hinder or contribute to” meeting Canada’s climate change commitments.So far, however, Canada has done little to define what the Paris Agreement entails for planning, assessment and decision making on projects and other undertakings with significant implications for meeting the Paris commitments. That leaves a serious gap in law, policy and practice between Canada’s commitments and the assessment of major undertakings.Assessments are an important venue for proactive climate change mitigation. They guide decision making on major extractive and infrastructure projects and other undertakings that will entrench existing practices or drive key transitions for many decades. If these assessments are to contribute to meeting our climate change mitigation commitments, we need to understand what meeting those commitments entails – how far we have to go and what we have to do to close the gap between our current efforts and our promised accomplishments.To inform serious efforts to fill that gap, this paper examines• what the Paris Agreement’s temperature goals imply for global and Canadian GHG reduction targets in light of “fair share” principles and feasible pathways;• what is needed to raise Canadian climate change mitigation ambitions to the Paris Agreement level, and ensure sufficiently strengthened and clarified targets, frameworks and applied tools to inform evaluations of particular undertakings; and• how to translate these needs and tools into well-specified and authoritative requirements for effective application under federal assessment law.Our intent has not been to deliver final answers but to establish a reasonably firm working base for comparing what we are doing with what is needed to meet our Paris commitments.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.114
Threshold uncertainty score0.827

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0100.004
Scholarly communication0.0160.004
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.095
GPT teacher head0.308
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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