Working words

Real-life lexicon of North American workers

Philip I Harber, Lori Crawford, Katie Liu, Levanto Schacter

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objective: This study describes a new computer methodology for analyzing workers' free text work descriptions. Methods: Computerized lexical analysis was applied to work descriptions of participants in the Lung Health Study, a smoking-cessation study in persons with early chronic obstructive pulmonary disease. Text was parsed and analyzed as single term roots and pairs of roots commonly occurring together. Results: The frequencies of terms reflect the work of a population; our subjects' most frequently used terms included "sale, office, service, business, engine[er], secretary, construct, driv[e], comput[e], teach, truck." Standard classification schemes (NAICS and SOC) and textbooks use terms inconsistent with those of actual workers. Many common empirical terms imply both industry and job information content, although traditional coding schemes separate industry and job title. Conclusions: Formal analyses of language may facilitate communication, identify translation priorities, and allow automated work coding.

Original languageEnglish (US)
Pages (from-to)859-864
Number of pages6
JournalJournal of occupational and environmental medicine / American College of Occupational and Environmental Medicine
Volume47
Issue number8
DOIs
StatePublished - Aug 2005
Externally publishedYes

Fingerprint

Industry
Textbooks
Motor Vehicles
Smoking Cessation
Chronic Obstructive Pulmonary Disease
Language
Communication
Lung
Health
Population

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

Cite this

Working words : Real-life lexicon of North American workers. / Harber, Philip I; Crawford, Lori; Liu, Katie; Schacter, Levanto.

In: Journal of occupational and environmental medicine / American College of Occupational and Environmental Medicine, Vol. 47, No. 8, 08.2005, p. 859-864.

Research output: Contribution to journalArticle

@article{731ec0a5d89b4d159cb70ac24df4ed66,
title = "Working words: Real-life lexicon of North American workers",
abstract = "Objective: This study describes a new computer methodology for analyzing workers' free text work descriptions. Methods: Computerized lexical analysis was applied to work descriptions of participants in the Lung Health Study, a smoking-cessation study in persons with early chronic obstructive pulmonary disease. Text was parsed and analyzed as single term roots and pairs of roots commonly occurring together. Results: The frequencies of terms reflect the work of a population; our subjects' most frequently used terms included {"}sale, office, service, business, engine[er], secretary, construct, driv[e], comput[e], teach, truck.{"} Standard classification schemes (NAICS and SOC) and textbooks use terms inconsistent with those of actual workers. Many common empirical terms imply both industry and job information content, although traditional coding schemes separate industry and job title. Conclusions: Formal analyses of language may facilitate communication, identify translation priorities, and allow automated work coding.",
author = "Harber, {Philip I} and Lori Crawford and Katie Liu and Levanto Schacter",
year = "2005",
month = "8",
doi = "10.1097/01.jom.0000169095.16779.66",
language = "English (US)",
volume = "47",
pages = "859--864",
journal = "Journal of Occupational and Environmental Medicine",
issn = "1076-2752",
publisher = "Lippincott Williams and Wilkins",
number = "8",

}

TY - JOUR

T1 - Working words

T2 - Real-life lexicon of North American workers

AU - Harber, Philip I

AU - Crawford, Lori

AU - Liu, Katie

AU - Schacter, Levanto

PY - 2005/8

Y1 - 2005/8

N2 - Objective: This study describes a new computer methodology for analyzing workers' free text work descriptions. Methods: Computerized lexical analysis was applied to work descriptions of participants in the Lung Health Study, a smoking-cessation study in persons with early chronic obstructive pulmonary disease. Text was parsed and analyzed as single term roots and pairs of roots commonly occurring together. Results: The frequencies of terms reflect the work of a population; our subjects' most frequently used terms included "sale, office, service, business, engine[er], secretary, construct, driv[e], comput[e], teach, truck." Standard classification schemes (NAICS and SOC) and textbooks use terms inconsistent with those of actual workers. Many common empirical terms imply both industry and job information content, although traditional coding schemes separate industry and job title. Conclusions: Formal analyses of language may facilitate communication, identify translation priorities, and allow automated work coding.

AB - Objective: This study describes a new computer methodology for analyzing workers' free text work descriptions. Methods: Computerized lexical analysis was applied to work descriptions of participants in the Lung Health Study, a smoking-cessation study in persons with early chronic obstructive pulmonary disease. Text was parsed and analyzed as single term roots and pairs of roots commonly occurring together. Results: The frequencies of terms reflect the work of a population; our subjects' most frequently used terms included "sale, office, service, business, engine[er], secretary, construct, driv[e], comput[e], teach, truck." Standard classification schemes (NAICS and SOC) and textbooks use terms inconsistent with those of actual workers. Many common empirical terms imply both industry and job information content, although traditional coding schemes separate industry and job title. Conclusions: Formal analyses of language may facilitate communication, identify translation priorities, and allow automated work coding.

UR - http://www.scopus.com/inward/record.url?scp=23644440094&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=23644440094&partnerID=8YFLogxK

U2 - 10.1097/01.jom.0000169095.16779.66

DO - 10.1097/01.jom.0000169095.16779.66

M3 - Article

VL - 47

SP - 859

EP - 864

JO - Journal of Occupational and Environmental Medicine

JF - Journal of Occupational and Environmental Medicine

SN - 1076-2752

IS - 8

ER -