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The O*NET content model

he Occupational Information Network (ONET) is a comprehensive database developed by the U.S. Department of Labor to replace the Dictionary of Occupational Titles (DOT). It offers detailed descriptions of over 900 occupations, including information on cognitive, interpersonal, and physical skill requirements, as well as working conditions. ONET's data is primarily derived from surveys of a large, representative sample of workers, ensuring its relevance and accuracy. While the database is extensive, some users have noted areas for improvement, such as clarifying underlying constructs and simplifying item wording. Despite these critiques, O*NET's data generally correlates well with wages, solidifying its value for researchers and professionals interested in labor markets.

The Occupational Information Network (O*NET), is a great database containing measures of occupational characteristics produced by the United States Department of Labor as a replacement for the Dictionary of Occupational Titles. O*NET scores cover cognitive, interpersonal, and physical skill requirements, as well as working conditions, and are derived mostly from survey responses of large, representative samples of workers. O*NET’s substantive scope and sampling are impressive, but there are also significant gaps and duplication in content. Underlying constructs, item wording, and response options are often vague or overly complex. However, O*NET items have generally sensible correlations with wages, which, along with the richness of the database, ensure O*NET’s place among researchers interested in work and labour markets.

Responding to methodological criticisms of the Dictionary of Occupational Titles (DOT) ( published by the U.S. Department of Labor in 1939 to assist the Employment Service in matching job-seekers to vacant positions during the Depression )and the costs of in-person job analysis, the Advisory Panel for the Dictionary of Occupational Titles (APDOT) was created in 1990 to consider alternatives. APDOT recommended the creation of a new system to replace the DOT, subsequently named the Occupational Information Network (O*NET), which would use standardized surveys of a representative sample of job incumbents instead of job analysts conducting workplace interviews and observations 

O*NET data collection and structure

The first complete O*NET cycle produced a database of 239 items across seven surveys mailed to employers for workers to complete and an additional questionnaire assigned to job analysts because the questions proved too abstract for job incumbents to answer (U.S. Department of Labor 2005, pp. A-4, A-9). The incumbent questionnaires are titled Education and Training, Knowledge, Work Activities, Work Context, Work Styles, and Skills. A small sample of job analysts complete the Abilities questionnaire based on written job descriptions and in 2008 assumed responsibility for the Skills questionnaire from job incumbents, creating a break in this series. These questionnaires cover different but sometimes overlapping substantive domains.Footnote1

To reduce respondent burden, individuals within occupations are randomly selected to receive a subset of questionnaire(s) requiring about a half-hour to complete, rather than completing all surveys.

O*NET content

There are 239 distinct items across all O*NET survey instruments, not counting the Background questionnaire. The Knowledge, Skills, Abilities, and Work Activities questionnaires ask two-part questions about both the Importance and Levels of a given skill or characteristic, such as the item on Negotiation below. These surveys account for 161 items or two-thirds of the total. In principle the different surveys cover different substantive domains, but in practice the division of labour between them is imprecise and the content overlapping. The size of the O*NET database and the looseness of its conceptual structure make it difficult to summarize the content parsimoniously, but Table 1 gives some indication of the major content areas covered by the different surveys.

The content is strong in a number of areas. The education and training items are crisp and thoughtful. The response options are detailed, easy for respondents to understand, and expressed in natural units, such as educational degrees and units of time.

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Content Courtesy : https://labourmarketresearch.springeropen.com

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