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2017· paratext· en· W4254121324 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsIndex (typography)MathematicsComputer scienceWorld Wide Web

Abstract

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Citation (2017), "Index", Age Diversity in the Workplace (Advanced Series in Management, Vol. 17), Emerald Publishing Limited, Bingley, pp. 189-193. https://doi.org/10.1108/S1877-636120170000017010 Publisher: Emerald Publishing Limited Copyright © 2017 Emerald Publishing Limited INDEX AAC. See Assimilative and accommodative coping (AAC) model Active aging, successful aging at work, 6 Activity theory, successful aging, 37, 41–43 Age and gender issues, in workplace influence of, 120 intersectionality, 121–123 linkages with work outcomes, 124–132 multiple identities, 123–124 relation to work outcomes, 127–129 shifting identity marker, 129 social identity, 121 Age-based income inequalities, 5 Age bias, behavioral component of, 102 Age discrimination, 169 Age discrimination climate, 102, 103 Age Discrimination in Employment Act, 1967, 15 Age-diverse organizations, knowledge sharing in, 170–179 Age-diverse workforce, 145–146 Age diversity, 95–96 beyond surface- categorization, 163–165 and deep-level categorization, 163–165 knowledge sharing, 165–169 tailoring HRM practices to improve knowledge sharing, 170–179 Age diversity climate (ADC) age-focused climate constructs, 101–104 age-focused concepts of, 99–104 analysis, level of, 104–109 definition, 97–101 evolution of, 97–99 HRM practices, 101 and measuring, 100–101 operationalization, 104–112 organizational identification, 101 psychological, 100–101 synthesis of, 105–108 Age identity, 125–127 Age-related changes cognitive changes, 146–147 crystallized intelligence (Gc), 147 fluid intelligence (Gf), 147 personality changes, 147 personality differences, 146–147 Age with job design, model integrating, 146–150 Age X job design interaction age and, 150–151 autonomy, 151–152 skill variety, 150–151 and task variety, 150–151 Aging process, 145–146 American Bureau of Labor Statistics projects (2012–2022), 172 Assimilative and accommodative coping (AAC) model, 38, 47 Australia in aging analysis of, 24–25 case study, 22 labor supply against demand, 21 labor supply scenario, 26 in work analysis of, 24–25 Australian Treasury’s (2015) Intergenerational Report (IGR), 10 Canada labor supply against demand, 16 labor supply scenario, 26 Categorization-elaboration model (CEM), 96, 168 China labor supply against demand, 19 labor supply scenario, 26 Chronological age, 145 Cognitive age, 127 Cognitive changes, 147 Continuity theory, successful aging, 41–43, 59 Degree of inclusion, 98 Disengagement theory, successful aging, 41–43, 59 Diversity climate, 110 Double standard of aging, 128 Employee attitudes, 148 Family-interference-with-work (FIW), 124 Felt age, 126 Feminine jobs, 120, 131 Functional age, 145 GDP growth function, 11 GDP per labor force participant, 12 Gender-based income inequalities, 5 Gender identity, 124–125 General Social Survey (GSS), 76 Generational cohorts membership, work-related outcomes, 69–71 psychological contracts, 72–75 and related empirical evidence, 68–72 silent, baby boomers, Gen X, and milennials, 68 Generational differences, 65–67 countervailing hypotheses, 75–85 generational cohorts and related empirical evidence, 68–72 psychological contracts, and the work context, 72–75 Germany labor supply against demand, 17–18 labor supply scenario, 26 Gerontological theories, successful aging activity theory, 37, 41–43 continuity theory, 41–43, 59 disengagement theory, 41–43, 59 Rowe and Kahn’s model, 36, 37, 43 Global Financial Crisis of 2008–2009, 23 Globalization increase in, global labor migrations, 8 and technological advances, 9 Global labor migrations, 14–15 globalization increase in, 8 Global population trends, 13–14 Good job design, 141 HRM practices assimilation phase, 176 familiarization phase, 176 HR planning, 170–171 and knowledge retention, 172–173 performance appraisal, 173–175 policies, 178 retirement planning, 172–173 reward systems, 178–179 separation phase, 176 team age composition, 171–172 training and development, 175–178 HR system, 162 Human capital theory, 164 Human resource management (HRM), 162 See also HRM practices IMF World Economic Outlook Database, 11 Inclusive climates, 98–99 Income inequalities age-based, 5 gender-based, 5 India labor supply against demand, 18 labor supply scenario, 27 Informal economy, 7 Information and communication technology (ICT), 6 Information and Decision-making Perspective (IDP), 165–166 Japan labor supply against demand, 20 labor supply scenario, 27 Job and work design, 140 psychological perspective of, 141–146 Job attitudes, 147 Job characteristics model (JCM), 141 Job demands-control model, 142 Job demands-resources model, 142 Job design, model integrating age with by age, 149 cognitive differences, 146–147 lifespan development theories, 147–148 and motivation, 147–148 and personality differences, 146–147 psychological implications for, 148–150 Job distress, 124 Job satisfaction, 66, 124, 144 Job stress, 66 Knowledge management processes, 165 Knowledge sharing age-diverse employees, 176 influence, 179 integrative view, 166–168 optimistic view, 165–166 pessimistic view, 168–169 tailoring HRM practices to improve, 170–179 Labor force participation, older workers Australian perspective, 12–13 globalization and technological advances, 9 globalization increase in, global labor migrations, 8 global labor migrations, 14–15 global population trends, 13–14 higher participation rates, 8 labor demand, 11–12 labor supply, 11 work and aging across industries, 23–24 work and aging in Australia, analysis of, 24–25 work structures, 8 Labor market discrimination, 5 Labor supply country scenarios, 26–28 and demand projections, 10 impact, 9 low-skill, 14 shortages, 6 Labor supply against demand Australia, 21 Canada, 16 China, 19 Germany, 17–18 India, 18 Japan, 20 South Korea, 20–21 United Kingdom, 16–17 United States, 15 Labor supply scenario Australia, 26 Canada, 26 China, 26 Germany, 26 India, 27 Japan, 27 South Korea, 27 United Kingdom, 28 United States, 28 Lifespan age, 146 Lifespan developmental theories of AAC model, 47 behavior–event contingencies, 46 comparison and critique of, 48–50 MTLD, 46–47 resource approach, 45 SAVI model, 48–49 SOC model, 45–46 SST, 47–48 Mentoring, 176, 177 Morgeson and Humprhey’s WDQ model, 143–144 Motivational theory of lifespan development (MTLD), 38, 46–47 MTLD. See Motivational theory of lifespan development (MTLD) National Population Census, 12 National Seniors Australia, 9 Occupational identity, 140 Old Age Security (OAS), 16 Older Workers Pilot Projects Initiative (OWPPI), 16 Organization for Economic Cooperation and Development (OECD), 4, 7–9 Organizational age, 146 Organizational age cultures, 103, 107 Organizational behaviors, 140, 147 Organizational Climate for Successful Aging (OCSA), 102, 103, 107 Organizational policy, 4 Paid employment, full-time/part-time, 6 Performance appraisal systems, 173–175 Personality changes, 147 Person-Environment (P-E) fit alpha level considerations, 79–81 cohort equivalency checks, 77–78 covariates, 79 data preparation and choice of analyses, 79 inclusion and sample representativeness, criteria for, 77 independent variables, 78 measures, 78–79 method, 76–77 negatively valenced affective outcomes, 84–85 positively valenced affective outcomes, 81–84 Population aging, workforce internationally, 5–7 Protected people from work, 4 Psychological age, 126–127 Psychological perspective, job and work design age-diverse workforce, 145–146 aging, 145–146 job design, approaches to, 143–145 mediating mechanisms, 149 moderating mechanisms, 149–150 worker well-being, 140, 142 Psychosocial age, 145 Public policy, 4 developed economies, 5 Re-employment programs, 7 Relational demography approach, 167 Reverse mentoring, 176, 177 Role theory, 142 Rowe and Kahn’s model, 36, 37, 43 SAVI model. See Strength and vulnerability integration (SAVI) model Selective optimization with compensation (SOC) model, 147, 148 lifespan developmental theories of, 45–46 successful aging, 42 Self-categorization theory, 167 Skilled migration programs, 7, 14 Skill variety, 150–151 SOC. See Selective optimization with compensation (SOC) model Socio-emotional selectivity (SES) lifespan theory, 163 Socioemotional selectivity theory (SST), 39, 47, 147, 148 SOC theory, 131 South Korea labor supply against demand, 20–21 labor supply scenario, 27 SST. See Socioemotional selectivity theory (SST) Stop-gap strategy, 5 Strength and vulnerability integration (SAVI) model, 39, 48–49 Successful aging, 36 AAC model, 38, 47 criteria and strategies for, 39 employees active role in, 40 gerontological theories, 36–43 lifespan developmental theories of, 43–50 MTLD, 38, 46–47 resource approach, 37 Rowe and Kahn’s model, 36, 37, 43 SAVI model, 39, 48–49 SOC model, 38, 45–46 SST, 39, 47 strategies, 55 theories overview of, 37–40 at work, 50–57 working definition and theoretical framework of, 40 Task variety, 150–151 Temporarily outsourcing, 5 Theory on age alpha level considerations, 79–81 choice analyses, 79 cohort equivalency checks, 77–78 covariates, 79 data preparation, 79 inclusion and sample representativeness, criteria for, 77 independent variables, 78 measures, 78–79 method, 76–77 negatively valenced affective outcomes, 84–85 positively valenced affective outcomes, 81–84 Transition To Retirement (TTR), 21 Underemployment, Global Financial Crisis of 2008–2009, 23 Unemployment rates, 8 United Kingdom labor supply against demand, 16–17 labor supply scenario, 28 United States labor supply against demand, 15 labor supply scenario, 28 older workers, 120 Unsuccessful aging, 43 US Department of Labor Women’s Bureau, 120 Value in diversity hypothesis, 165 Work design, 140 Work design model, 152–155 Worker behavior, 144 Worker well-being, physical and psychological, 140, 142 Workforce aging, 4–5 protected people from work, 4 Workplace age diversity, 162 Workplace Intergenerational Climate Scale (WICS), 103, 108 Work, successful aging at comparison and critique of, 54–57 criteria and strategies for, 51–52 employees active role in, 54 working definition and framework of, 52–54 Book Chapters Prelims Part I Framing Age and Age Diversity in Organizations Chapter 1 The Workforce Demographic Shift and the Changing Nature of Work: Implications for Policy, Productivity, and Participation Chapter 2 Successful Aging at Work and Beyond: A Review and Critical Perspective Chapter 3 Generational Differences: Effects of Job and Organizational Context Chapter 4 A Conceptual Framework of Age Diversity Climate Part II Age Diversity at Work. Rethinking Organizational Practices Chapter 5 The Intersection of Age and Gender Issues in the Workplace Chapter 6 Job Design and Older Workers Chapter 7 Enhancing Knowledge Sharing in Age-Diverse Organizations: The Role of HRM Practices Index

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.281
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0020.001
Scholarly communication0.0100.008
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7190.714

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.303
GPT teacher head0.485
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
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