Board Leadership Database (U.S. Public Firms) + ML Script for Scaling Human Coded Data

Joseph S. Harrison; Matthew A. Josefy; Matias Kalm; Ryan Krause

doi:10.5281/zenodo.7304697

Board Leadership Database (U.S. Public Firms) + ML Script for Scaling Human Coded Data

Joseph S. Harrison^*, Matthew A. Josefy, Matias Kalm, Ryan Krause

^*Corresponding author for this work

Information Systems & Oper. Mgt.

Research output: Online publication or Non-textual form › Database

Abstract

Files include an open sourced database of CEO duality and board chair orientations developed by scaling up human coded data using supervised machine learning techniques, as well as the accompanying code to scale human coded data. Users may apply the code to score the same variables from company proxy statements or may adapt it and retrain models to scale human coded data of other constructs or measures.

Original language	English
Media of output	Online
DOIs	https://doi.org/10.5281/zenodo.7304697
Publication status	Published - 2022

Access to Document

10.5281/zenodo.7304697Licence: CC BY

1 Article

Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context
Harrison, J. S., Josefy, M. A., Kalm, M. & Krause, R., Jul 2023, In: Strategic Management Journal. 44, 7, p. 1780-1802
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
13 Citations (Scopus)

432 Downloads (Pure)

Cite this

@misc{ceecd000e2684e00aaab5557cc04427b,

title = "Board Leadership Database (U.S. Public Firms) + ML Script for Scaling Human Coded Data",

abstract = "Files include an open sourced database of CEO duality and board chair orientations developed by scaling up human coded data using supervised machine learning techniques, as well as the accompanying code to scale human coded data. Users may apply the code to score the same variables from company proxy statements or may adapt it and retrain models to scale human coded data of other constructs or measures. ",

author = "Harrison, {Joseph S.} and Josefy, {Matthew A.} and Matias Kalm and Ryan Krause",

year = "2022",

doi = "10.5281/zenodo.7304697",

language = "English",

}

TY - ADVS

T1 - Board Leadership Database (U.S. Public Firms) + ML Script for Scaling Human Coded Data

AU - Harrison, Joseph S.

AU - Josefy, Matthew A.

AU - Kalm, Matias

AU - Krause, Ryan

PY - 2022

Y1 - 2022

N2 - Files include an open sourced database of CEO duality and board chair orientations developed by scaling up human coded data using supervised machine learning techniques, as well as the accompanying code to scale human coded data. Users may apply the code to score the same variables from company proxy statements or may adapt it and retrain models to scale human coded data of other constructs or measures.

AB - Files include an open sourced database of CEO duality and board chair orientations developed by scaling up human coded data using supervised machine learning techniques, as well as the accompanying code to scale human coded data. Users may apply the code to score the same variables from company proxy statements or may adapt it and retrain models to scale human coded data of other constructs or measures.

U2 - 10.5281/zenodo.7304697

DO - 10.5281/zenodo.7304697

M3 - Database

ER -

Board Leadership Database (U.S. Public Firms) + ML Script for Scaling Human Coded Data

Abstract

Access to Document

Fingerprint

Research output

Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context

Cite this