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Record W3204728815 · doi:10.1017/s0003975622000194

Executive Pay: Board Reciprocity Counts

2022· article· en· W3204728815 on OpenAlexfundno aff
Olivier Godechot, Joanne Horton, Yuval Millo

Bibliographic record

VenueEuropean Journal of Sociology · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersYork UniversityHarvard University
KeywordsReciprocity (cultural anthropology)Executive compensationMandateAccountingBusinessCorporate governancePolitical sciencePsychologyFinanceLawSocial psychology

Abstract

fetched live from OpenAlex

Abstract We study the influence of the corporate board network on executive pay for 3,395 US firms between 1990 and 2015. We identify three elementary structures through which the interlocking network reflects forms of inter-group reciprocity across firms:restricted exchange, when two executives sit on each other’s respective boards;delayed exchange, whenysits on the board ofxafter the end ofx’s mandate on the board ofy; andgeneralized exchange, whenxsits on the board ofy, who sits on the board ofz, who sits on the board ofx. These ties, which are overrepresented, are related to higher executive pay, but are not related to firm performance, which we interpret as a form of rent extraction. We use the Sarbanes-Oxley Act (2002) as a natural experiment to confirm our results. The impact on pay disappears after 2004, once these types of exchanges are constrained.

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)0.004
metaresearch head score (Gemma)0.041
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.024
GPT teacher head0.216
Teacher spread0.192 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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