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Record W7134248662 · doi:10.24926/265535.4317

Public Law, Private Platforms

2023· article· W7134248662 on OpenAlexaboutno aff
Andrew Keane Woods

Bibliographic record

VenueMinnesota law review · 2023
Typearticle
Language
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
Fundersnot available
KeywordsStatutory lawScholarshipPrivate rightsState (computer science)Legal aspects of computingQuarter (Canadian coin)Constitutional lawAction (physics)Criminal lawScrutiny

Abstract

fetched live from OpenAlex

Our law—both our constitutional law and much of our statutory law—has long drawn a fraught distinction between public and private domains. Indeed, debates about the public/private distinction date as far back as liberalism itself. But today’s private digital platforms strain that distinction to a new degree. Platforms have become our public spaces, but because they are privately owned and “merely” coordinate private ordering, they operate without the guardrails of many of our most important laws. For example, anti-discrimination law once covered nearly all short-term bookings at inns and hotels; today, nearly a quarter of the hospitality market is controlled by Airbnb, where the majority of bookings are in owner-occupied homes that are exempt from anti-discrimination law’s reach. The First Amendment once protected against the gravest threats to free speech; today, scholars question whether it is fit to handle the novel speech problems presented by social media. The Fourth Amendment once prevented the police from gaining warrantless access to our most private information; today, the police simply buy that data on the open market. The list goes on. While criminal law and speech scholars have noticed the state action problem in constitutional law, and civil rights scholars have discussed the private carveouts in anti-discrimination law, there is little scholarship moving beyond these silos to explore how these different regulatory puzzles stem from the same fundamental problem. Recognizing that the public/private distinction is the core of the platform problem has a number of implications. It helps explain the platforms’ persistent ability to evade meaningful regulation and it suggests a new way forward—a more suitable remedy than using blunt antitrust tools to address our biggest social ills. Specifically, courts and legislators should revive and expand the legal doctrines that recognize the imperfect nature of our law’s distinction between public and private. These private-but-public doctrines—like public accommodations, the public policy doctrine in contract, the public trust doctrine in property, and more—have long recognized the limits to private ordering in the public interest. It is time to update them for the digital age.

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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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: Review · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0260.086

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 head0.160
GPT teacher head0.327
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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