Covid-19 Impact on Employment and Skills for the Labour Market

Enfield, Sue

doi:10.19088/k4d.2021.081

Cited by 10 publications

(11 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, there is a cultural value, which is an important factor to consider regarding unemployment in Nigeria. Cultural practices in Nigeria do not favor women in terms of employment compared to their western counterparts (Enfield, 2019). Furthermore, it is widely believed and supported in many parts of the country that women cannot inherit their parents' properties because they are expected to marry into another family and receive whatever they require from that new family.…”

Section: Related Workmentioning

confidence: 99%

Analysing Factors Influencing Women Unemployment Using a Random Forest Model

2023

HKJSS

View full text Add to dashboard Cite

The unemployment crisis has been a persistent issue for both developed and developing countries, resulting in an economic indicator deficit. Women are at a disadvantage and continue to encounter significant obstacles to gaining employment. Nigeria, like many other developing countries with high unemployment rates, has a 33% unemployment rate. Consequently, there has been minimal research on the factors that affect women's unemployment. As a result, the purpose of this study investigates the factors that influence women's unemployment in Nigeria. Although the Random Forest model has been widely applied to classification issues, there is a gap in the literature's use of the random forest as a predictor for analyzing factors influencing women's unemployment. The random forest model was employed in this study because of its characteristics such as strong learning ability, robustness, and feasibility of the hypothesis space. As a result, the Random forest prediction model was benchmarked with seven different cutting-edge classical machine learning prediction models, which include the J48 pruned tree, Support Vector Machine, AdaBoost, Logistic Regression, Naive Bayes, Logistic Model Tree, Bagging, and Random Forest. The experimental results demonstrate that Random Forest outperformed the other seven machine learning classifier models using ten commonly used performance evaluation metrics. According to the study's findings, age groups, ethnicity, marital status, and religion were the essential factors affecting women's unemployment in Nigeria.

show abstract

Section: Related Workmentioning

confidence: 99%

Analysing Factors Influencing Women Unemployment Using a Random Forest Model

2023

HKJSS

View full text Add to dashboard Cite

show abstract

“…The complex mosaic of ACL institutions, 20 years ago, played an essential role in developing and delivering specialist provision for such vulnerable groups and fortunately some survived and continue this vital work, but current conditions require an expansion in learning support for disadvantaged groups. One of the limitations of this study is its focus on experience in England, but the same need for adult education is even more apparent in middle-income countries, where COVID-19 has had a high negative impact on the informal sector and those in precarious employment (Enfield, 2021). England has had a major influence on education and training in other countries (Tūtlys et al.…”

Section: Retrospective Assessment and Conclusionmentioning

confidence: 99%

Vulnerable workers and the demise of adult education in England

Wallis¹,

Nacua²,

Winterton³

2021

View full text Add to dashboard Cite

PurposeThis paper reviews changing government policy on adult education in England over the past 20 years and the funding regimes affecting adult and community learning and union-led learning, which play a major role in learning opportunities for socially excluded adults.Design/methodology/approachA review and analysis of extant literature, informed by previous involvement in the sector and ongoing collaborations.FindingsTwo decades ago, adult education in England provided a variety of learning opportunities for people who either had limited qualifications or who needed to reskill for whatever reason. Access to those opportunities has been reduced just when it is most needed.Research limitations/implicationsThis is a review and viewpoint paper based on experience in England, the limitations of which are discussed in the concluding section. Notwithstanding the institutional specificities of adult education in England, many of the implications are generic and have wider relevance beyond this country context.Practical implicationsEconomic recovery post-coronavirus (COVID) and Brexit will require more access to adult education so people can prepare for labour market re-integration. The practical implication of extending provision in adult education to support labour market integration of vulnerable workers is relevant to most countries.Originality/valueThis paper takes a holistic view of adult education, with particular attention to adult and community learning and union-led learning.

show abstract

“…The labour market outlook due to the pandemic is uncertain. Recovery from the virus occurs in different ways and at different times in the market (Enfield, 2021). In post-Covid Europe, the situation varies from country to country due to different economic and social developments (Bieszk-Stolorz & Dmytrów, 2022).…”

Section: Labour Marketmentioning

confidence: 99%

Impact of COVID-19 on labour force and recovery peculiarities in selected countries of Europe

Conigliani¹,

Iorio²,

Monni³

2023

JESI

View full text Add to dashboard Cite

In this paper, we have examined the impact of COVID-19 on labour force and recovery peculiarities in selected countries of Europe. Our goal has been to reach patients with post-COVID-19 or long-COVID-19 symptoms who were treated since 2020 and latest 2021 in different medical spas around Europe. Our research focused on whether work affects any aspect of life during illness and whether complaints experienced during post-COVID-19 treatments affect any aspect of life during illness. To achieve our results, we used quantitative research and tested two hypotheses. Our primary survey was conducted in May-June 2022. A total of 110 valid responses were received. The data collected through the questionnaire was examined using statistical analysis and calculationsdescriptive statistics, oneway ANOVA, linear regression analysis. All the respondents had COVID-19 positive test results in their life and attended post-COVID treatments in different medical spas in Europe. The results showed that coronavirus symptoms (post-or long-COVID-19 syndrome) were most likely to interfere with social and leisure activities and work. Well-being and pain need improvement. Improvement is possible with spa rehabilitation packages offering complex interventions such as balneotherapy (which uses local natural resources such as natural healing water, peloids, mofette), climatotherapy, physiotherapy, occupational therapy, and physiotherapy. Working during illness has a significant impact on quality of life. It also has an impact on daily activities, mobility, and pain. Working during illness (COVID-19 infection) affected all aspects of life, and patients perceived that illness-related disturbances mainly affected work performance.

show abstract

Covid-19 Impact on Employment and Skills for the Labour Market

Cited by 10 publications

References 2 publications

Analysing Factors Influencing Women Unemployment Using a Random Forest Model

Analysing Factors Influencing Women Unemployment Using a Random Forest Model

Vulnerable workers and the demise of adult education in England

Impact of COVID-19 on labour force and recovery peculiarities in selected countries of Europe

Contact Info

Product

Resources

About