MétaCan
Menu
Back to cohort
Record W2891479420 · doi:10.6084/m9.figshare.8006312

Climate risk perceptions in the Ontario (Canada) electricity sector

2019· dissertation· en· W2891479420 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2019
Typedissertation
Languageen
FieldEnvironmental Science
TopicClimate Change and Sustainable Development
Canadian institutionsnot available
Fundersnot available
KeywordsElectricityClimate changePerceptionBusinessGeographyEnvironmental planningEngineeringPsychologyEcologyElectrical engineeringBiology

Abstract

fetched live from OpenAlex

This thesis examines management cognition of climate risks in the electricity sector in Ontario (Canada).Risk perception literature is combined with corporate adaptation and risk management literature to offer a broad conceptual framework of climate risk readiness among power producers and utilities. This research aims to move management cognition of climate change past prior contributions which considered climate risk as being solely physical in nature. In this work, eight exogenous and endogenous factors relating to climate risk are examined for their influence on how management may view a wider spectrum of climate change impacts. Using an inductive research approach, 20 in depth case studies explore how electricity executives/senior managers perceive those risks using construct elicitation (repertory grid technique). Findings are triangulated with a narrative analysis of their corporate reportage of climate risks, to gain deeper insight into the complex phenomena of climate risks for the sector.Findings show some similarities and some appreciable differences in both groups’ view of climate risks despite their legitimately contending positions in industry. Overall both power producers and utilities are predominantly concerned with risk analysis and assessment of climate related risks, and less with risk response, suggesting at present the sector remains in an analytical state. The potential benefits of this research approach will provide useful insights to multiple groups including managers and policy makers.<br>

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.6190.003

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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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