MétaCan
Menu
Back to cohort
Record W7132954549

Hedging the Planet: The Demand for Global Governance in Sustainable Finance

2024· dissertation· W7132954549 on OpenAlexfundno aff
Christian Morin Elliott

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEconomics, Econometrics and Finance
TopicSustainable Finance and Green Bonds
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsAmbiguityCorporate governanceCollective actionAction (physics)ScholarshipFinancial marketSustainabilityFinancial services
DOInot available

Abstract

fetched live from OpenAlex

Sustainable finance governance, or the rules and processes by which the financial sector navigates issues like climate change, has seen enormous expansion over the last twenty years, with over one hundred related global initiatives launched. Counter to what existing scholarship might predict, financial institutions have been participating, by the thousands, in efforts governed by high-profile environmental authorities with little sway over traditional financial affairs. This dissertation seeks to understand why financial actors participate, and why some more than others. I approach these questions in three movements, first focusing on national contexts, then organizational perspectives, and finally, public policy processes. In this first movement, I deductively derive hypotheses and use quantitative analysis to examine patterns of industry-wide participation at the country level. I find that wealthier liberal market economies with more environmental NGOs tend to precipitate greater initiative involvement, but much of the overall variation is not explained at the national level of analysis. To go beyond the limitations of existing explanations in the literature, the second and third movements of the dissertation proceed abductively in a theory-building exercise, bringing together concepts and qualitative data to make sense of the phenomenon. At the organizational level, I argue that financial actors seek out collective action to navigate the ambiguity and uncertainty that environmental problems create for the economy. Collective action distributes high-fixed costs, brings in external expertise to bolster credibility, and mitigates the risks of being singled out for failure. Whether a given organization seeks to innovate new responses depends on the stakeholder pressures they experience to act on these issues, relative to the adjustment costs that searching for solutions and implementing them entails. I evaluate this argument using four comparative initiative cases: the Paris Aligned Investment Initiative, The Net Zero Asset Managers Initiative, The Net-Zero Banking Alliance, and the Net-Zero Insurance Alliance. In the final empirical movement, I investigate the role of public policy in creating demand for initiatives. I argue that, in a positive feedback dynamic, participation trends increase the likelihood that a governmental response on sustainable finance issues materializes, which in turn can position initiatives as means of compliance, preemption, or venues to assist in navigating new rules. I demonstrate the validity of this argument, and the mechanisms by which such a process occurs, using the case of the European Union’s Action Plan on Financing Sustainable Growth, from 2014-2022. In total, this dissertation contributes to understanding conditions for business power in emerging issue areas, the forces driving the politics of sustainable finance, and the interactions between public and private authorities in evolving regime complexes.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.017
Scholarly communication0.0130.017
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicSustainable Finance and Green BondsFrench-language works237,207