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Legal Mind at the Helm: General Counsel in Top Management and Firm Innovation

2024· article· en· W4400442022 on OpenAlex
Seung‐Hwan Jeong, Xingyuan Fei, Sean Cao, Lynn Li

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

VenueAcademy of Management Proceedings · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Law and Ethics
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsBusinessLaw and economicsManagementEconomics

Abstract

fetched live from OpenAlex

General Counsels (GCs), who traditionally were seen as legal gatekeepers playing a supporting role, are increasingly ascending to more powerful roles in strategic leadership. Considering their expanding role, we examine how general counsels in top management teams (TMTs) influence firm strategy in the critical realm of innovation. Our main argument is that the presence of GCs in TMTs can ensure that legal expertise is leveraged in the early stages of the innovation process, allowing for inventions to be developed with a clear understanding of legal implications. In support of this idea, we find that firms with GCs in TMTs have better innovation performance (in terms of both quantity and quality), and this result is stronger when firms’ innovation efforts entail high legal risk and uncertainty. Furthermore, the results are weaker when GCs’ attention is diverted due to ongoing patent litigation and stronger when GCs have higher levels of power within the TMT.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.261
Teacher spread0.236 · 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