MétaCan
Menu
Back to cohort
Record W3130675220 · doi:10.1257/mic.20200474

Targeted Product Design

2023· preprint· en· W3130675220 on OpenAlex
Heski Bar‐Isaac, Guillermo Caruana, Vicente Cuñat

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Economic Journal Microeconomics · 2023
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMonopolistic competitionMonopolyDuopolyRobustness (evolution)Product designIndustrial organizationProduct (mathematics)MicroeconomicsEconomicsComputer scienceCompetition (biology)Risk analysis (engineering)BusinessMathematicsCournot competition

Abstract

fetched live from OpenAlex

We propose an intuitive representation of product design in which firms locate inside a circle and consumers in its outer circumference. Designs trade off horizontal and vertical transport costs. Our setting encompasses all linear demand rotations. Firms with lower quality or higher marginal costs choose niche designs that cater to specific consumers at the expense of alienating the rest. Firms choose intermediate designs or more polarized ones, instead, depending on the convexity of the vertical transport cost. We examine such design choices in monopoly, duopoly, and monopolistic competition settings. (JEL D21, D24, D42, D43)

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.019

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 head0.050
GPT teacher head0.246
Teacher spread0.197 · 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