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Record W4417088674 · doi:10.1093/cmlj/kmaf023

Sustainable investment management in Canada

2025· article· en· W4417088674 on OpenAlexaffabout
Douglas Sarro

Bibliographic record

VenueCapital Markets Law Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Ottawa
FundersUniversity College London
KeywordsSustainabilityAsset (computer security)Investment (military)DiscretionGovernment (linguistics)Asset managementAction (physics)

Abstract

fetched live from OpenAlex

Abstract Canadian law likely requires asset managers with discretion over client funds to consider the sustainability impacts of their investment decisions, but there is little to no case law elaborating on this obligation—perhaps due to procedural barriers to litigation in this field. Managers of publicly traded collective investment schemes must disclose material information on how sustainability factors influence their investment decisions, but Canada’s provincial and territorial securities regulators have stopped short of standardizing these disclosures. Nonetheless, asset managers can draw on a wealth of commentary and soft law to harmonize their disclosure practices and adapt their investing approaches to better reflect the financial and other challenges posed by climate change and other threats to environmental sustainability. The likelihood that Canada’s federal government will make greater use of its own powers to drive financial sector action on sustainability gives asset managers reason to be proactive in this vein.

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)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.210
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0140.004
Scholarly communication0.0070.001
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.000

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 head0.005
GPT teacher head0.232
Teacher spread0.227 · 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
GenreEmpirical

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
Published2025
Admission routes2
Has abstractyes

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