Notice bibliographique
Résumé
Citation (2017), "Index", Factors in Studying Employment for Persons with Disability (Research in Social Science and Disability, Vol. 10), Emerald Publishing Limited, Bingley, pp. 273-282. https://doi.org/10.1108/S1479-354720170000010012 Publisher: Emerald Publishing Limited Copyright © 2017 Emerald Publishing Limited INDEX AbleData, 255 Ableist attitudes, of employees, 161 Accelerated technological change, 251 Accelerating transformation, 134 Accessibility, 250–251, 254, 255, 263 Accommodations, 168 actual and unknown costs, 172 lack of, 183 uncertainty of, 159 Activities of daily living (ADLs), 207, 214 ADLs. See Activities of daily living (ADLs) Adolescent, results of studies, 195 AHS data, 71 American Community Survey (ACS), 12, 250 American economy, 251 American Housing Survey (AHS), 37, 39 Americans with Disabilities Act of 1990, 4, 83, 158, 252, 254 Artificial intelligence (AI), 261 Asthma, 84 Autism spectrum disorder (ASD), 198 Average marginal effects (AME), 12 Awareness program, 148 Behavioral concerns, 159 Best practices, 157, 160, 164, 166, 168, 169, 172 Biopsychological model, 132 Black employees, 139, 148 Business Administration, 137 Canada’s employment rate, 156 Canadian Association for Community Living 2010, 183 Canadian business leaders, 159 Census Region, 40 Center for Epidemiological Studies Depression Scale (CES-D), 213 Certificate primary school, 101 secondary school, 93, 104 Chronic diseases, 84, 112 disabilities, 91 women with, 102 Civil Rights Act of 1964, 4, 252 Climate diversity, 162 Collective beliefs, 160 Commission on Employment Equity (CEE), 129 Community inclusion, 227 Convention on the Rights of Persons with Disabilities (CRPD), 149, 165 Corporate commitment, 168 Corporate culture change, 160, 161, 168, 174 beliefs and culture, 158–163 business case for hiring persons with disabilities, 163–164 coworker attitudes, 168–171 disability employment improvement, 173 employees, 172–173 implications for research, 174 integrating employees with disabilities, 156 leadership, from top, 167–168 methodology, 157–158 organizational values, 158–163 recruitment, 171–172 supervisor attitudes, 168–171 Corporate social responsibility (CSR), 157, 164–167 Corporate values, 162 Currently Population Survey (CPS), 6 analyses of, 8 Annual Social and Economic Supplement data, 12 descriptive statistics, 13 Demographic variables, 228 Department of Labor, 36 Depressive symptoms, 207, 209, 213, 220 partial correlation matrix, 215 structural equation model, 217 Disabilities, 84, 250–251 attitudes, 256–257 binaries, 128 bio-psycho-physio-pathology of, 147 and complexity, 258–261 definitions of, 16 and earned income, 51–52 and employment, 251 enhanced telecommunications, 255–256 experienced labor market disadvantages, 16 future of work, 261–263 gendered effects of, 8, 10–12 identification, 229–230 increasing demands, for human capital, 257–258 inequality, 9 labor market outcomes, 7 legal changes impact/technological advances, 250 men, employment/income, 16 rights movement, 259 role of technology, 255 self-care, 40 by sex, 90 Social Model approach, 227 status, 213 structural equation model, 217 supply and demand side, 6 types of, 142 women economic inequalities, 4 employment and income, 16 equal rights and antidiscrimination legislation, 4 labor market barriers, 4 work limiting, 12 persons reporting percentage, 15 Disability awareness, 138 committees, 175 Disability Visibility Project, 23 Disabled participants report, 233 Disabled workers, 168 Discrimination, legal protections, 252 Diversity management, 161, 169 Dunedin Committee on Aging (DCoA), 228 Dunedin residents, 242 Dunedin study participants characteristics and representativeness, 229 Earned income, 37, 38, 40, 41, 44–51, 52–55, 62–66, 68–69 car ownership, 55–57 children under age, 5, 52–54 demographic profile, 41–44 and disabled children, 55 Earnings employed men/women with disabilities disadvantages, 20 gaps, 4 income (See Earned income) linear regression models, 20 disability status and gender, 21–22 percent difference, by disability status and gender, 23 women with disabilities, earnings of, 210 Economic dependency, 36 Economic disadvantage, 227, 239, 240, 241, 243, 245 Economic inequality, gender/disability, role of, 9 Economic resources, 232, 233, 239, 241, 242 discretionary spending, money for, 232 home rental vs. ownership, 233 household income, 232 mediating effects of, 242 Economic self-sufficiency, 71 Educational attainment, 15, 26, 57 Education levels, 101 and cause of daily limits, 94 EEO laws, 252 Employer preferences, 6 Employers’ attitude, 84 Employment agencies, 171 benefits of, 182 circumstances, 206 disability, 251 indicator of successful transition, 182 logistic regression models, 16 by disability status and gender, 17–18 rates by disability status and gender, 19 rates for women without disabilities, 16 social and economic level, 182 Employment Equity Act (EEA), 129, 130, 149 Employment opportunities, 147 Employment rates, 16, 95, 156 Employment strategies, 169 Employment trends of persons with disabilities, 141 Equal employment opportunity (EEO) policies, 252 Equity employees, 149 European Network for Corporate Social Responsibility and Disability, 166 Experience, lack of, 183 Family Employment Awareness Training (FEAT) program, 191 Federal Housing Administration (FHA), 38 Feminization of employment norms, 10 Firm size, 15 Florida, community-wide survey, 227 Functional impairment, vii, viii, ix, x, 227, 229, 230, 241, 243, 244 Gender disabilities by, 140 disadvantage of, 10–11 employment, quantitative labor market research, 8 earnings gap, 4, 23, 92 employment relations, 10 hypothesized associations, 216 as moderator, 209–210 supply and demand side, 6 General Managers, 167 Government employee, 15 GPS, 261 Great Recession, 36, 41 Gross domestic product (GDP), 129, 183 Guidelines for Critical Review Form – Quantitative Studies , 186 Handicapped Children Act, 256 Health care, 251 Health/disability, demographic profile, 51–52 Health problems, daily activities, 91 High school diploma, 104 Hiring persons, 171 with disabilities, 165 Households, earned income of, 52 Housing and Urban Development (HUD), 36 administrative data, 69 administrative records, 38 assisted housing, 36 programs, 38 assisted housing work, 37, 38–39 car ownership, 55 demographic profile, 41–44 demonstrations, 37 earned income for household heads, 66 economic self-sufficiency, 71 health/disability status, 65 predictors of receipt of earned income, 69 SNAP (food stamp) benefits, 58 socioeconomic status (SES), 70 young adults, 41 average educational attainment of, 41 characteristics of, 58–63 earned income receipt, predictors of, 63–67 young householders, 53 comparison of, 53–54 Housing assistance, 39 Housing subsidy, 38 HUD. See Housing and Urban Development (HUD) Human capital, 257 IDL. See Independent living or self-care (IDL) Independent living or self-care (IDL), 14 limitation, 14 Individuals with Disabilities Education Act (IDEA), 256, 262 Information and communication technology (ICT), 253 Institutional Review Board (IRB), 228 Instrumental activities (IADLs), 207, 214 Internal human resource systems, 138 International Classification of Functioning, Disability and Health (ICF), 81, 132 capability approach, 82 Internet medium, 256 Intersectionality, 8–12 disadvantage, multiple dimensions of, 9 labor market inequalities, 8 Italian National Institute of Statistics (ISTAT), 86 ISTAT, 2004, 93 IT- SILC, 2004, 83, 92–94 Job market conceptual framework, 81–82 data source, 86–87 disability, and employment, 93–97 disabled people, sub-sample of, 103 multinomial/sequential logit models, 110–114 sequential logit model, for working conditions, 104–110 disabled population in Italy, 115 estimation results, probit regression model, 97–102 evidence, 89–93 Italy, legislation on disability, 85–86 literature review, 82–84 methodology, 87–89 Jobs, 263 autonomy, 207, 214, 215, 218, 221 characteristics, 209 structural equation model, 217 choice, 8 composition and educational requirements of, 253 creativity, 214, 218, 221 market (See Job market) placements, in labor market, 199 position, for disability people, 96 switch, 253 Knowledge gained, 194, 196, 197 Labor force participation, 4, 6 Labour force, 102 employment, 80 multinomial logit model, 89 participation, 97 willingness to participate, 82 Labour market, 10, 80, 253 activity, 10 British, 103 disability laws, implementation of, 109 disadvantage for people with mental health, 82 double discrimination, 101 full-time/part-time, 107 impact of disability on willingness, 85 inequalities, 8 Italian data set, 81 needs, 262 outcomes, 7, 8 disability, gendered effect of, 8 outcomes of persons, 81, 82 participation, 80 research, 25 worse education, outcome of, 102 Larry Greiner’s Model, 131 Learnerships, 135, 137, 147 Legal protections, against discrimination, 252 Legislation concerning employment protection, 85 Lewin’s model, 131, 132 LGBQT status, 10 Limited awareness, 168 Linear regression models, 20 Living in Ireland Survey, 2000, 82 Location, demographic profile, 44–51 Logistic regression models, 63 Low-wage jobs, 37 Management practices, 157, 161, 162 Managerial commitment, 173 Marital status, 15, 88, 101, 103, 120 Maximum Likelihood, 65–67 estimates, analysis of, 67, 69 function, 88 Medical advances, 251 Mental health, 207, 210 Mentors, 159, 170 skills of, 171 Mentorship, 197 Miami-Dade County demographic structure, 211 Miami-Dade County population, 211 Miami-Dade County residents, 211 Mobility, 11, 40, 84, 87, 90, 93, 103, 115, 157, 214, 253, 255, 256, 258, 260, 263 Mobility impairments, 87, 90, 255, 256 Modern discrimination, 5 Mplus software, 214 Multidisciplinary vocational rehabilitation intervention, 191 Multinomial logit model, 110, 111–112 alternative, 113–114 Multinomial logit tree, 110, 113 Multiple disabilities, 6, 9, 12, 14, 16, 20, 22, 24 Multiple regression, 240 National Health Interview Survey (NHIS), 12 National Longitudinal Transition Study of Special Education Students, 71 National Qualifications Framework (NQF), 137 Netcare, 139 case study, 134 disability integration program, 144 draft disability strategy, 135 education, 148 processes, 131 New York City, 39 Nondisabled group, 84 Nondisabled people, in strict sense, 92 Non-Hispanic black/white, 13, 15, 18, 21, 211, 214 Non-standard work arrangements, 7 Occupational therapist, 189, 191 OECD countries, 85 Online survey, 228 Ordinary least squares (OLS) regression, 12 Organizational citizenship behaviors, 160 Organizational culture, 145–147, 161, 260 Organizational development (OD) model, 131 Organizational justice, 144, 145 Participation, in social recreational, 227 Partnerships, 138 Partnership status, 231 who do/do not identify, as disabled, 236–237 with/without functional impairments, 234 Part-time employment, 107 Physical disabilities, 207, 208, 209, 210, 212, 215, 218–221. See also Vocational intervention future research, 200 limitations, 199 participant characteristics, 187 review of, 198–199 skills/knowledge gained, 197 studies characteristics, 187 characteristics/overview of, 188 results of, 194–196 vocational intervention characteristics, 187 vocational programs common components of, 192–197 employment achievement, 197 employment, knowledge/perceptions of, 198 youth, vocational interventions, 182 Physical impairments, 141 Physical/mental disability, 82 Planned behavior theory, 158 Poverty, 36–38, 40, 129, 146, 253 AHS data, 71 deep, 41 Great Recession, 41 for women, 10 Predicted probability, 12 Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA), 184 Pre-labor market inequalities, 26 Pre-work training, 172 Principles on Business and Human Rights, 165 Probit models, marginal effects, 99–100 Probit regression model, 97 PsychInfo, 184 Psychological disabilities, 170 Public assistance, 5 Public Housing Authorities (PHAs), 37, 38 admission policies, 71 Public policies, 259 Quantitative labor market, 8 Race, 5, 9, 25, 26, 63, 64, 68, 70, 128, 133, 136, 139, 140, 146, 148, 161, 210–214, 217, 228, 243, 252 disabilities by, 140 ethnicity, 214 Reasonable accommodation, 142, 143 Recruiting policy, 171 Rehabilitation Act of, 1973, 252, 256 Rental housing, 45, 51 Response, categories, 232 Retention rates per program, 137 Rust Belt, 71 Safety, pre-employment training, 173 Scholars interest, 9 Scopus, 184 Search terms, overview of, 186 Self-sufficiency, 36, 37 economic, 36 Self-sufficiency programs, 70 SEM analysis, 216 Senior management, 167 Sensitive groups, 162 Sensory, 87 limitations, 16 Sequential logit model, 88, 89, 97, 104, 105–106 multinomial, comparison, 110–114 for working conditions, 104–110 Sequential logit tree, 88 alternative, 107–109 Siebers theory, 133 Sinako initiative, 145 Sinako Project, 137 Skilled labor, 258 Skills, 197 employment-related, 198 through learnerships, 147 Skills Development Act (SDA), 129, 130 Smart phones, 261 SNAP (food stamp) benefits assistance, 44 housing and urban development, 58–60 program, 70 Social activities, 182 Social disadvantage, 227 Social inclusion, 233, 241, 242 level of social/recreational/community participation, 231–232 mediating effects of, 241, 242 partnership status, 231 perceived stigma, 232 Social interaction, 170 Socializing, with friends/neighbors, 231 Social justice, 128 Social model, 81, 244 approach, to disability, 227 claims, 227 of disability, 226, 258 Social participation, 262 Social practices, 9 Social relationships, 169, 182 Social responsibility, 128 Socioeconomic disadvantage, 8 Socioeconomic status (SES), 70 South Africa democratically elected government, postcolonial-post-apartheid, 129 Integrated National Disability Strategy, 130 with Netcare, 138 South African organizations, 147 South African Qualification Authority’s (SAQA), 137 SSSI eligibility, 83 Stereotyping, 168 Subjective well-being, 227, 230–231, 233, 240, 241, 242, 243 Survey of Income and Program Participation (SIPP), 39 Systematic review process, flow of studies, 185 Tech Act, 255 Technology Assistance for Individuals with Disabilities Act of 1988, 255 TedWomen Talk, 5 Time limits, 71 Total household income, 239 Training applicants, 172 to develop employable skills, 183 employment or vocational, 184 Transformational leadership, Netcare CEO, 145 Transition probabilities, 81 t-tests, 233 Turkish hospitality industry, 163 Uberization, 251 Uber’s smartphone app, 251 United States institutional, demographic and economic changes, 252 post-industrial information-based economy, 250 technological innovation, 251 US Business Leadership Network’s Disability Equality Index, 166 U.S. Census Bureau, 250 US Census estimates from 2010, 206 University degree, 104 Variables, 12, 14, 16, 19, 20, 38, 62, 64, 65, 68, 70, 80, 83, 89, 97, 98, 101, 103–105, 110, 112, 211, 213–215, 227–229, 233, 238, 240, 244, 259, 260, 263 description, 98 explanatory, 98 Vocational agencies, 173 Vocational interventions, 183, 186. See also Physical disabilities characteristics, 187 search terms, overview of, 186 study characteristics, 187 vocational programs common components of, 192–197 employment achievement, 197 employment, knowledge/perceptions of, 198 Vocational programs, 198 Vocational rehabilitation program, 189–190 physical disabilities, youth, 182 Voluntary transition, 7 Wage gap, gender, 4 Washington Group Series, 230, 244 Web of Science, 184 Welfare, demographic profile, 51–52 Well-being, 227 participants who do/do not identify, as disabled, 236–237 participants with/without functional impairments, 234 psychological, 208, 209 analytic strategy, 214–215 covariates, 214 depressive symptoms, 213 disability status, 213 functional limitation, 213 gender, 214 job autonomy, 214 job creativity, 214 limitations of, 220, 221 measures, 213 study procedures/sample, 210–212 work characteristics, 218, 219 subjective, 230–231, 240, 241, 242, 243, 245 WGS functional impairments, 238, 239 functional limitation, 233 Windows, 95, 256 Wisconsin Center for Education Research, 260 Within-group disparities, 9 Women experience, disadvantages, 7 Work characteristics, 216, 218 supply and demand side, 6 work-effort, 6 Workforce access, 263 Workforce participation, 231, 233, 250, 252, 260 Workforce risks, 253 Working conditions, 209, 210, 212, 219, 220, 221 Working environments, 85 Working hours, by sex, 95 Working situations, 88 Work, in post-industrial society, 252–254 Work-limiting disabilities, 12, 14, 19, 20 percentage of persons reporting, 15 Workplace, disability inclusion complexity definition, 132–134 implications for practice, 149–151 Lewin’s change model, 132 methodology, 130–131 Netcare case, 134–149 contradictions of, 144 disabilities, types of, 139–144 education and awareness program, 148 monitoring/evaluation, 138–139 persons, challenges limiting employment of, 135–136 question of intersectionality, 148–149 refreezing, 139 transforming, 137–138 unfreezing, 135 policy-practice gaps, 130 postcolonial-post-apartheid South Africa, 129 social justice issues, 128 Workplace discrimination, 244 Work requirements, 71 Work schedules, 254 World Health Organization’s (WHO), 130, 156 World Health Survey, 156 Young Millennials, 70 Youth with disabilities, 182 with physical disabilities, 182, 183 survey participants, 238 vocational interventions with physical disabilities, 182 Book Chapters Prelims Part 1 Relationship of Gender and Other Sociodemographics to Work Role Chapter 1 Employment Outcomes Among Men and Women with Disabilities: How the Intersection of Gender and Disability Status Shapes Labor Market Inequality Chapter 2 Who Got Earned Income? Health and Other Barriers to Employment for Young Millennials in HUD-Assisted and Other Rental Housing Chapter 3 To What Extent does Disability Discourage from Going on the Job Market? Evidence from Italy Part 2 Disability Inclusion Strategies and Interventions Chapter 4 The Complexity of Disability Inclusion in the Workplace: A South African Study Chapter 5 Model of Successful Corporate Culture Change Integrating Employees with Disabilities Chapter 6 A Systematic Review of Vocational Interventions for Youth with Physical Disabilities Part 3 Work Role and Well-Being Chapter 7 People with Physical Disabilities, Work, and Well-being: The Importance of Autonomous and Creative Work Chapter 8 Disability and Community Life: Mediating Effects of Work, Social Inclusion, and Economic Disadvantage in the Relationship Between Disability and Subjective Well-Being Part 4 The Future of Work Chapter 9 Disability and the Future of Work: A Speculative Essay About the Authors Index
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,008 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,010 | 0,008 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,755 | 0,765 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».