MétaCan
Menu
← Back to cohort
Record W6959691302 · doi:10.11575/prism/39448

Comparing Alberta's Major Cities: A Framework for Evaluating the Sufficiency of Urban Climate Mitigation Plans

2021· other· en· W6959691302 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2021
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
Fundersnot available
KeywordsBlueprintGreenhouse gasClimate changeAction planClimate change mitigationOrder (exchange)Climate policyGlobal warming

Abstract

fetched live from OpenAlex

This paper examines the climate plans of two cities in the heart of Canada’s fossil fuel producing region, and evaluates their sufficiency. It makes two contributions to the discussion of public policy aimed at mitigating the impact of climate change: first, it develops a framework for evaluating urban climate plans, which helps us to judge whether these plans offer a blueprint for meaningful action. Second, it contributes to our understanding of Alberta’s ability to contribute to Canada reaching its GHG reduction targets. Finding that only Calgary’s plan is insufficient, Calgary may want to consider reorienting their actions in order to meaningfully contribute to climate change mitigation, and could follow Edmonton’s example on how to do this. By 2017, the world was 1.0ºC warmer than its pre-industrial level; it is projected to reach 1.5 ºC warming between 2030 and 2052 if nothing changes the current rate of warming.1 The impacts of reaching 1.5ºC are understood and thus can be planned for, whereas there is high uncertainty associated with exceeding this limit. In order to adapt to the anticipated impacts of climate change, the planet must act to limit warming to 1.5ºC. The path forward requires urgent mitigation – meaning the global reduction of greenhouse gas emissions. Leadership is thus needed from all levels of government; however, policy makers face critical challenges when it comes to action. These challenges can be summarized into three key problems. First, overly-cautious action is weak without targeting the root causes. Second, action taken thus far does not reflect the urgency of the issue. Third, action is taken in short-term, piece-meal steps. In general, these problems can manifest as gaps between the solution this problem requires, the solutions that are chosen, and lack of progress to date. There are two types of climate action: adaptation and mitigation. Adaptation involves actions taken to prepare a place and population for the anticipated impacts of climate change; while mitigation includes actions to reduce greenhouse gas emissions. While it’s true that climate action ultimately must be wide-spread, long-term and systemic –actions will differ depending on the context. Actions can be analyzed according to region, level of government, or activity type. The global conversation on climate change is led by nations. Comparatively, cities are much less-visible and yet critically important. Municipalities have their own unique roles in mitigating climate change based on their proximity to individuals and the concentration activity. Approaching climate mitigation requires focusing on the smaller components without losing sight of the global context. This project will focus on local municipal governments but assess their individual mitigation actions against a broader concept of sufficiency. Two Canadian cities, Calgary and Edmonton, will be used in this analysis. To assess their actions, this project will review each city’s climate mitigation action plan. Within this assessment of each plan, emphasizing the transportation 4 sector serves two purposes. First, activities related to passenger transportation are some of the highest sources of greenhouse gas emissions. However, the reasons why transportation is such a high emitter have to do with its connections to the root causes of the problem. Therefore, the second purpose is to use transportation as a way to reflect how well the plan considers root causes.

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)0.029
metaresearch head score (Gemma)0.057
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.183
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.057
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0220.022
Science and technology studies0.0070.009
Scholarly communication0.0150.005
Open science0.0040.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.057
GPT teacher head0.332
Teacher spread0.275 · 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
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen MIND→Same topicGenetic Mapping and Diversity in Plants and Animals→French-language works237,207→