TY - JOUR
T1 - Working words
T2 - Real-life lexicon of North American workers
AU - Harber, Philip
AU - Crawford, Lori
AU - Liu, Katie
AU - Schacter, Levanto
N1 - Funding Information:
Supported by the American Association of Medical Colleges/National Institute for Occupational Safety and Health/Centers for Disease Control and Prevention [#MM0060 02/02], National Cancer Institute [1RO1 0H3839–01]; Division of Lung Diseases, National Heart, Lung, and Blood Institute, National Institutes of Health [Lung Health Study-Contract N01-HR-46002]
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.
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U2 - 10.1097/01.jom.0000169095.16779.66
DO - 10.1097/01.jom.0000169095.16779.66
M3 - Article
C2 - 16093937
AN - SCOPUS:23644440094
SN - 1076-2752
VL - 47
SP - 859
EP - 864
JO - Journal of occupational and environmental medicine
JF - Journal of occupational and environmental medicine
IS - 8
ER -