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Record W4238686043 · doi:10.32920/ryerson.14646570.v1

The electric utility of the future: insights on challenge and change in Ontario LDCs

2021· preprint· en· W4238686043 on OpenAlexaboutno aff
Nabila Alibhai

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningConstruct (python library)BusinessPropositionGovernment (linguistics)Influencer marketingMarketingIndustrial organizationDistribution (mathematics)SociologyComputer science

Abstract

fetched live from OpenAlex

The traditional role of electric utilities is diminishing in the face of technology, customer, financial, regulatory, and policy changes occurring in the industry. These changes will determine the future viability of local distribution companies [LDCs] in Ontario. A diverse collection of academic, industry, and government literature supports varying opinions of what the LDC of the future should look like. A historical overview and an institutional theory of organizational behaviour method frames the idea that technological innovation can break through the sector’s historically and culturally embedded resistance to change. A two-stage survey method is used to construct a dialogue between key players, and finds support for the above proposition from the expert judgements of LDC decision-makers and influencers. The new energy customer, empowered by new energy technologies, is a primary causal factor of the challenges in the sector, and also of the transformative change needed to create the LDC of the future.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.732

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0140.008
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.232
Teacher spread0.186 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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