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Record W2153748865

Pots and Kettles: Governance Practices of the Ontario Securities Commission

2005· preprint· en· W2153748865 on OpenAlexaffabout
Joel Fried

Bibliographic record

VenueScholarship@Western (Western University) · 2005
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Regulation and Crises
Canadian institutionsWestern University
Fundersnot available
KeywordsCorporate governanceCommissionAccountingBusinessPublic sectorPrincipal (computer security)CashPrivate sectorPublic administrationFinanceEconomicsPolitical scienceEconomyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

An analysis of the governance policies of the Ontario Securities Commission (OSC) is undertaken in light of that institution's drive to improve governance practices in the private sector.It turns out that the Commission itself does not practice many of the governance practices required and/or advocated for the corporate sector.Furthermore it is argued that governance policies necessary to resolve the principal -agent problem for the corporate sector are necessary to resolve that problem for a public sector regulator, but they are not sufficient.This is the result of the greater difficulty in monitoring the regulator because the objectives of the principals/electorate are more difficult to measure than profits, and those objectives are only loosely correlated with cash flows.The insistence on publicly available cost-benefit analyses for new and existing OSC initiatives is one method to improve monitoring.

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)0.003
metaresearch head score (Gemma)0.012
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: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.006
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.133
GPT teacher head0.300
Teacher spread0.167 · 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
Published2005
Admission routes2
Has abstractyes

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