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Record W6969583772 · doi:10.5683/sp3/sfyabx

Canadian Climate Policy Inventory

2024· dataset· en· W6969583772 on OpenAlexafffundabout

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusSt. Francis Xavier UniversityUniversité du Québec à MontréalCarleton UniversityWestern UniversityMemorial University of NewfoundlandUniversity of ReginaCanadian Climate ForumUniversity of British ColumbiaSimon Fraser UniversityMcGill UniversityUniversité du Québec à ChicoutimiUniversity of New BrunswickUniversity of SaskatchewanUniversity of VictoriaUniversity of CalgaryRoyal Roads UniversityUniversity of Alberta
FundersAlberta Real Estate FoundationSocial Sciences and Humanities Research CouncilMitacsGovernment of Canada
KeywordsClimate changeSubsidyGovernment (linguistics)General partnershipRenewable energyPolicy analysisClimate change mitigationGreenhouse gas

Abstract

fetched live from OpenAlex

This dataset contains a comprehensive and comparable database of Canadian emissions reduction policies across federal, provincial and territorial orders of government. The dataset comprises two database files (both .csv and .xlsx formats) in English and French. Source data is primarily in text format and from a variety of government and non-government sources. These sources include federal biennial reports to the United Nations Framework Convention on Climate Change (UNFCCC); provincial, territorial, and federal climate plans; and past work by Navius Research Inc. and the Canadian Climate Institute to build a Canadian climate policy tracker. Policy information is converted into textual categories in the database according to the codebook developed by the research team and attached to this dataset. Relevant policies are those targeting climate change mitigation (e.g., emissions reductions such as emissions pricing or the Clean Fuel Regulations), and policies to change energy use and sources (e.g., subsidizing renewable energy sources). This database is a project of the Canadian Climate Policy Partnership (C2P2). The goal of C2P2 is to inform smart, coherent and new policy options to meet Canada’s net zero transition by engaging in data-driven research on and analysis of climate policies in Canada, and supporting such activities in a broader network of researchers. For more information on C2P2, please visit the project webpage: https://spp.ucalgary.ca/research-publications/canadian-climate-policy-partnership-c2p2. The project README file contains further information on data format and versioning practices. Further details about C2P2 and the database can be found in a methodology paper, available in English only, published in Canadian Public Policy. It is also available on the Social Science Research Network (SSRN). An abridged methodology document, available in both English and French, is available on PRISM, the institutional repository of the University of Calgary. Both are linked in the Related Publications section of the database metadata.

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)0.002
metaresearch head score (Gemma)0.010
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.104
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0100.034
Science and technology studies0.0040.000
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1040.036

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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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
GenreDataset

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
Published2024
Admission routes3
Has abstractyes

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