Using occupational information to increase vocational differentiation

1992 ◽  
Vol 19 (1) ◽  
pp. 3-12
Author(s):  
Margaret A. Moore ◽  
Greg J. Neimeyer
Keyword(s):  
Occupational Information ◽  
Vocational Differentiation

Employers and the 1881 Population Census of England and Wales

2015 ◽  
pp. 29-49 ◽  
Author(s):  
Robert J. Bennett ◽  
Gill Newton
Keyword(s):  
Systematic Error ◽  
Size Distribution ◽  
Firm Size ◽  
Extraction Method ◽  
Building Industry ◽  
Population Census ◽  
Firm Size Distribution ◽  
England And Wales ◽  
Occupational Information ◽  
First Results

This article presents the method and first results of using the 1881 England and Wales Census Enumerators' Books (CEBs) to identify and extract employer records using occupational information. Over 230,000 employers are identified, of which about four fifths employ others. Important sub-groups are also identified of the own account selfemployed, company proprietors, directors and partnerships. The article demonstrates the feasibility of the method and uses the example of the building industry to illustrate firm-size distribution at parish level across England and Wales. The paper indicates the applicability of the extraction method to other censuses, which is now possible using the recently released I-CeM database. The paper also demonstrates some difficulties in the database for 1881, including data keying and coding errors, ranging from 0.5 to 5.5 per cent of entries for larger businesses. Gender miscoding appears to be a systematic error of about 0.7 per 1,000 people. The analysis suggests that where small or atypical sample groups are involved, users of the census database should make detailed checks with manuscript CEBs.

scholarly journals P.2.38 Occupational exposure and incidence of asthma based on prescription of drugs

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A97.1-A97
Author(s):  
Jesper Bælum ◽  
Lars Rauff Skadhauge ◽  
Trine Thilsing ◽  
Jesper Rønhild Davidsen ◽  
Øjvind Omland ◽  
...  
Keyword(s):  
Lung Diseases ◽  
Register Data ◽  
Low Molecular Weight ◽  
Job Exposure Matrix ◽  
Cleaning Agents ◽  
Occupational Information ◽  
Incident Asthma ◽  
Changes In Risk ◽  
Incident Cases ◽  
Prevalent Asthma

Prescription of drugs for obstructive lung diseases (ATC code R03) has previously been shown to be an indicator of actual asthma. In this cohort study, we have combined occupational information with data from redeemed prescriptions between 2000 and 2013 extracted from the National Danish Prescription register.In 2003 a total of 7255 persons aged 20 and 44 years fulfilled a questionnaire, which among other things, included information on their longest held job. The jobs of 6470 were coded according to ISCO-88 and an asthma Job Exposure Matrix (JEM) was applied. Prevalent asthma was defined as at least two redeemed prescriptions of a R03 drug within 2 years. Incident asthma between 2003 and 2013 was defined as not having redeemed a R03 prescription in the previous years. Data was analyzed separately for each gender using multivariate logistic regression and presented as odds ratios (OR) with 95% confidence intervals (CI).Among those having a job 327 (5.1%) were identified as incident cases and 467 (7.2%) as prevalent cases. In females increased incidences were seen in exposures to reactive low molecular weight (LMW) substances (OR1.47 (95% CI 1.04–2.07)), cleaning agents (OR 1.52 (1.05–2.18)), metals (OR 3.31 (1.63–6.64)), while increased prevalence was seen with mite exposure (OR 4.41 (1.74–11.2)) and irritant gases (OR 1.76 (1.16–2.69)). In males no increased incidences were seen and only an increased prevalence with mixed environments (OR 2.24 (1.13–4.43)).In jobs increased prevalence and incidence were seen in female cleaners and drivers. Increased prevalence was seen in male printing workers.Meaningful associations with well-known asthmagenic exposures in young adults with asthma can be identified in administrative register data, and implementing the analyses of register data from larger populations will have the power to detect potential increased risks due to rare exposures or changes in risk over time.

Ballot Cues, Business Candidates, and Voter Choices in Local Elections

2020 ◽  
pp. 1532673X2094355
Author(s):  
Brian E. Adams ◽  
Edward L. Lascher ◽  
Danielle Joesten Martin
Keyword(s):  
Experimental Data ◽  
Decision Making ◽  
Business Owners ◽  
Small Business Owners ◽  
Local Elections ◽  
Electoral Success ◽  
Political Experience ◽  
Occupational Information ◽  
Political Background ◽  
Occupational Background

American voters commonly express abstract support for candidates with a business background, yet there is minimal systematic evidence about whether it advantages candidates in actual electoral contests. We examine this question using observational data, drawing on a California law allowing candidates to designate their occupational background on the ballot, and experimental data. Candidates with a business background are prevalent in California. However, neither of our studies indicate that business candidates enjoy atypical overall electoral success (although Republican leaning constituencies have a notably more favorable view of such candidates). A political background predicts electoral success far more effectively. Further, “small business owners” have more success than other business candidates, suggesting that voters consider the specifics of a candidate’s business experience. These results advance our knowledge of decision making in low-information elections, how voters weigh private-sector versus political experience, and how they filter occupational information through a partisan lens.

OCCUPATIONAL INFORMATION State by State

1960 ◽  
Vol 8 (4) ◽  
pp. 227-234 ◽  
Author(s):  
CHARLES R. FOSTER ◽  
JAMES DUNCAN
Keyword(s):  
Information State ◽  
Occupational Information

Automation in Colombia: assessing skills needed for the future of work

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael Jones ◽  
Sandra Idrovo-Carlier ◽  
Alfredo J. Rodriguez
Keyword(s):  
Design Methodology ◽  
Interpersonal Relationship ◽  
Political Factors ◽  
Content Type ◽  
Work Activities ◽  
Occupational Information ◽  
Occupational Information Network ◽  
Workforce Skills ◽  
The Usa ◽  
Automation Technology

PurposeThe purpose of this paper is to identify workforce skills that protect an occupation from elimination due to automation technology.Design/methodology/approachThe authors apply a Gaussian process (GP) classifier, based on the level of non-automatable work activities in an occupation, to USA and Colombian occupational datasets.FindingsThe authors find that communication, interpersonal relationship management and decision-making skills are most important in occupations that are resistant to automation.Research limitations/implicationsThe results are based on work activities data from the Occupational Information Network (O*NET) database developed for the USA labor market. This dataset does not capture significant differences in work activities, where they exist, for the same occupation between the two countries. The findings are also limited to Colombia. Readers should be careful to extrapolate the findings outside of this geography.Originality/valueThe authors discover that automation is likely to be a global phenomenon that can only be slightly mitigated by cultural and political factors.

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