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Record W2518570066 · doi:10.1257/aer.20161492

Certified Random: A New Order for Coauthorship

2018· article· en· W2518570066 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican Economic Review · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicGame Theory and Applications
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research ChairsNational Science Foundation
KeywordsAlphabetOrder (exchange)Computer scienceCertificationNorm (philosophy)First orderMathematical economicsOperations researchEconomicsMathematicsLinguisticsPolitical scienceLawManagementPhilosophyApplied mathematics

Abstract

fetched live from OpenAlex

Alphabetical name order is the norm for joint publications in economics. However, alphabetical order confers greater benefits on the first author. In a two-author model, we introduce and study certified random order: the uniform randomization of names made universally known by a commonly understood symbol. Certified random order (i) distributes the gain from first authorship evenly over the alphabet; (ii) allows either author to signal when contributions are extremely unequal; (iii) will invade an environment where alphabetical order is dominant; (iv) is robust to deviations; (v) may be ex ante more efficient than alphabetical order; and (vi) is no more complex than the existing alphabetical system modified by occasional reversal of name order. (JEL A14, Z13)

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical · Consensus signal: none
Teacher disagreement score0.765
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.009

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 head0.228
GPT teacher head0.466
Teacher spread0.239 · 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