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Record W3122744194 · doi:10.1257/mic.3.4.1

Platform Siphoning: Ad-Avoidance and Media Content

2011· article· en· W3122744194 on OpenAlexaff
Simon P. Anderson, Joshua S. Gans

Bibliographic record

VenueAmerican Economic Journal Microeconomics · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsProfitability indexContent (measure theory)AdvertisingBusinessQuality (philosophy)MathematicsPhysics

Abstract

fetched live from OpenAlex

Content providers rely on advertisers to pay for content. TiVo, remote controls, and pop-up ad blockers are examples of ad-avoidance technologies that allow consumers to view content without ads, and thereby siphon off the content without paying the “price.” We examine the content provider's reaction to such technologies, demonstrating that their adoption increases advertising clutter (leading to a potential downward spiral), may reduce total welfare and content quality, and can lead to more mass-market content. We cast doubt on the profitability of using subscriptions to counter the impact of adavoidance.(JEL L82, L86, M37)

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0200.001

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 head0.048
GPT teacher head0.189
Teacher spread0.141 · 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 designObservational
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

Citations87
Published2011
Admission routes1
Has abstractyes

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