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Record W3027392423 · doi:10.60082/2817-5069.3487

Antitrust Law in the New Economy by Mark R Patterson

2020· article· en· W3027392423 on OpenAlexvenueno aff
Thomas Dicsi

Bibliographic record

VenueOsgoode Hall law journal · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCapitalismProtectionismMonopolyLawDoctrineGovernment (linguistics)EconomicsPolitical scienceLaw and economicsEconomic historyInternational tradePhilosophyMarket economyPolitics

Abstract

fetched live from OpenAlex

THE DRAFTERS OF THE SHERMAN ANTITRUST ACT of 1890 would understandably be perplexed by the complexity of modern economic systems. These drafters, including the Act’s namesake, US Senator John Sherman, were operating in a world where protectionist economics dominated. Karl Marx had just recently completed his critique of untethered capitalism, Das Kapital, and international trade was largely confined to the exchange of raw materials. These drafters were responding to an issue very topical to the late-nineteenth century— John D. Rockefeller’s monopoly over American oil. The situation came to a head in 1882 when Samuel Dodd, the attorney to Rockefeller’s company, Standard Oil, ingeniously used the doctrine of trusts to consolidate all of Rockefeller’s oil holdings—representing 90 per cent of the market—under a single controlling trust. It took the government 21 years to successfully use the Act to dismantle Rockefeller’s Standard Oil Trust.

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: Review · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.203
Teacher spread0.178 · 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
GenreReview

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
Published2020
Admission routes1
Has abstractyes

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