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The purpose of this paper is to investigate the potential of already existing skills and competence ontologies to benefit European transparency tools and especially the implementation of the European Qualification Framework. Furthermore, it asks whether any of them could serve as a starting point to develop an International Standard Classification of Skills and Competences to supplement ISCED and ISCO.

This contribution contains a comparative analyses of three systems providing ontologies of skills and competences – DISCO, O*NET and Taxonomy_DB – under terminological and pragmatic aspects.

The analysis identifies O*NET as the most promising candidate to serve European transparency instruments and the EQF. Furthermore, it demonstrates that the development of an International Standard Classification of Skills and Competences, that is suitable for statistical purposes as well as appropriate for practical applications in human resource management and in the area of education, would have to integrate very diverging demands, which so far are being best met by O*NET and DISCO.

The depth of the analysis is not sufficient to serve as an exhaustive guideline to design an International Standard Classification of Skills and Competences.

The paper shows the potential of a future International Standard Classification of Skills and Competences for the EQF, for European transparency tools, and for statistical purposes.

This article brings a new topic, namely ontologies for skills and competences, into the European debate about competences and their visibility and validation.

The purpose of this chapter is to assess the importance of individual social capital characteristics in determining wages, both directly through their valuation by employers and indirectly through their impact on individual occupational choice. We find that a person’s level of sociability and care for others works through both channels to explain wage differences between social and nonsocial occupations. Additionally, expected wages in each occupation type are found to be at least as important as a person’s level of social capital in choosing a social occupation. We make use of restricted 2000 Decennial Census and 2000 Social Capital Community Benchmark Survey.

The purpose of this paper is to examine the impact of the substantial expansion in the labour force between 1997 and 2004 on the proportion of the Irish workforce that can be categorised as working in knowledge occupations.

The Quarterly National Household Survey was used to estimate the trend in knowledge type work at the national level for the period 1997 to 2004, specifically examining which specific occupations are increasing over this period.

Employment growth occurred relatively equally at the high‐, middle‐ and low‐skill occupational levels, indicating the continuing importance of intermediate and particularly low‐skill occupations in the structure and expansion of the Irish labour force.

There are substantial problems with the use of broad occupational level data as a proxy to measure the extent of knowledge occupations. It would be useful to consider adopting the Australian Standard Classification of Occupations as it includes the complexity of the set of tasks involved in a job, formal education, training and previous experience.

The findings indicate the continuing importance of intermediate and low‐skill occupations as well as high‐skill occupations in the structure and expansion of the Irish labour force. Government training and education policy needs to target resources across a broad range of skills and occupations.

The paper provides a profile and analysis of occupational changes in the Irish labour market.

Gauges of the extent of the managerial hierarchy drawn from occupational classifications appear to promise a comprehensive and precise overview of cross‐national comparative developments in work organisation. This paper considers the plausibility of the national historical shifts apparent from such gauges, and explores their comparative relation to alternative indications of work organisation, focusing on the experience of eleven advanced industrialised nations in the post‐war period. It shows that whilst it is clear that in the cases of some nations such gauges meaningfully express at least the comparative extent of managerial hierarchies, it is equally clear that for other nations they do not. The paper concludes that occupational classifications are no basis for inferences about comparative developments in the extent of managerial hierarchies, still less work organisation.

There is renewed interest in the professions as a range of occupations pursue professionalisation projects. The purpose of this paper is turn analysis to an important omission in current research – the skills deployed in the work of these professions. Such research is necessary because skills determine the formal classification of occupations as a profession.

Drawing on qualitative research, this paper explores the deployment of skills in work of one newly professionalised occupation in the UK’s National Health Service – physiotherapists.

The findings point to a disconnect between how this occupation has become a profession (the skills to get the job, and related political manoeuvring by representative bodies) and the mixed outcomes for their skills deployment (the skills to do the job) in work as a profession.

The paper provides missing empirical understanding of change for this new profession, and new conceptualisation of that change as both symbolic and substantive, with a “double hybridity” around occupational control and skill deployment for physiotherapists as a profession.

This article discusses the professional status of civil defense and protection agents and coordinators in Brazil, their working conditions and demands for professionalization in disaster risk management.

Two online surveys with operators and civil defense and protection managers and documentary analysis based this research. The first survey engaged 1,933 participants who provided information about the working conditions at municipal civil defense, while the second involved 1,344 civil respondents who assessed their roles and duties in disaster risk management.

Civil defense and protection agents pointed to the high turnover in these positions as the main factor for setbacks in disaster risk reduction, allied to precarious working conditions, lack of training, and unclear responsibilities in disaster risk management.

This paper contributes to the international debate on the professionalization of civil defense and protection and disaster risk management, bringing some insights from the sociology of professions. It has a policy impact of suggesting pathways to the inclusion of civil defense and protection in the Brazilian Occupational Classification to advance professional patterns and public recognition of disaster risk management careers.

This paper aims to discuss a new source of data detailing state level occupational licensing requirements for 50 professions.

This study's research team gathered state level licensing requirements for 50 profession in all 50 states and DC from 2022 to 2023. The authors include the type of regulation, entry requirements like fees, education, training, good moral character provisions and renewal requirements. The authors include Standard Occupational Classification industry codes to allow researchers to merge it with other publicly available data sources. Finally, the authors present descriptive statistics and provide a comparison of licensing requirements for audiologists, an occupation with variation in entry requirements.

The mean number of the 50 professions licensed in states is 36. On average, these professions require a bachelor's degree, $271 in licensing fees and 26 h of continuing education to renew. For the audiologist profession, there is considerable variation between states in entry requirements like fees and education.

Despite a large body of work on occupational licensing, data limitations still exist. Most analysis focuses on whether a profession is licensed or not. However, there is considerable variation between states for the same profession, providing an avenue for work estimating the effects of specific licensing requirements. A new source of data is introduced and discussed for researchers to use in future analyses of occupational licensing.

In an examination of class inequality in education in the Republic of Ireland over the period from the late 1990s to the mid 2000s, this chapter reveals class inequality in educational outcomes within social groups as well as across social groups, and places particular attention on the non-manual group. Within this group, a clear distinction can be made between those classified as having an ‘intermediate non-manual’ position and those classified as holding an ‘other (lower) non-manual’ position in terms of their educational performance at secondary education and subsequent access to higher education, which persists over the period. This finding has been revealed by disaggregating the non-manual group into the ‘intermediate non-manual’ and ‘other (lower) non-manual’ groups, a practice that has not been used by analysts in the past in the Irish context. In this chapter, we engage with theories of class which offer a framework for understanding educational inequality and in particular, why members of the same social class groups experience different educational outcomes.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

The purpose of this study was to investigate occupational and non-occupational mortality among Mexican immigrants in the South Eastern United States. The construction industry has the highest burden of occupational fatalities in the USA of all industries, and foreign-born Hispanic workers are disproportionately affected.

Data were obtained from 3,093 death certificates maintained by the Consulate General of Mexico in Atlanta, Georgia. Standardized mortality ratios (SMR) were used to compare occupational-related deaths among construction industry occupations, and logistic regression models were used to examine the relationship between manners of death not related to occupation and employment in the construction industry.

The proportion of Mexican immigrants who died from occupational injuries is higher among all construction workers (SMR = 1.31), roofers (SMR = 2.32) and carpenters (SMR = 2.25) than other workers. Among the population in this analysis suicide [adjusted odds ratio (aOR) = 0.63] and death from natural causes (aOR = 0.70) were inversely related to work in the construction industry.

Interventions to reduce occupational fatalities among Mexican migrant construction workers should target roofers and carpenters. Future research should further investigate the industry’s association with suicide and natural death.

This is one of the first analyzes that investigated associations between construction industry employment and non-occupational fatalities among immigrants. The analysis provides evidence that a large portion of the Mexican immigrant population is used in the construction industry (38%) and face elevated risks for occupational fatalities and the results of this investigation should encourage greater surveillance of occupational illness and injury among foreign-born immigrants who work in construction, as well as other high-risk industries.