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Record W3135912348 · doi:10.60082/2817-5069.3638

Corporate Friction: How Corporate Law Impedes American Progress and What To Do About It by David Yosifon

2021· article· en· W3135912348 on OpenAlexvenueno aff
Cameron Teschuk

Bibliographic record

VenueOsgoode Hall law journal · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsnot available
FundersFoundation for Research, Science and Technology
KeywordsCorporate governanceCorporationArgument (complex analysis)ShareholderStakeholderCorporate lawShareholder primacyLaw and economicsPerspective (graphical)Corporate securityCorporate communicationStakeholder theoryBusinessPolitical scienceAccountingLawEconomicsManagement

Abstract

fetched live from OpenAlex

David Yosifon's first book, Corporate Friction: How Corporate Law Impedes American Progress and What To Do About It, provides a unique perspective on the corporate purpose debate. The corporate purpose debate can be summarized as a search for the answer to a seemingly rudimentary question: “For Whom is the Corporation Managed”? Yosifon presents a well-researched argument that U.S. corporations should be managed for the best interest of stakeholders, opposed to shareholders. This distinction is known as the shareholder-stakeholder best-interest trade-of. Yosifon supports his argument with a refned analysis of the assumptions and norms that have led to a shareholder-centric model of corporate governance in the United States and its impact on “American progress.”

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)0.011
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: Other · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.014
Scholarly communication0.0090.011
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.225
Teacher spread0.187 · 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
GenreOther

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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