Bibliographic record
Abstract
Citation (2019), "Index", Swailes, S. (Ed.) Managing Talent: A Critical Appreciation (Talent Management), Emerald Publishing Limited, Bingley, pp. 163-165. https://doi.org/10.1108/978-1-83909-093-620201012 Publisher: Emerald Publishing Limited Copyright © 2020 Emerald Publishing Limited INDEX ‘A’ Players, 71–72, 74 Academic-practice gap, 35 Accidental manager, 4, 77–79, 82–83 AMO theory, 92, 95 Assessment centres, 58–60, 66–67 Assessment panels, 65 Bias, 21, 25, 53, 66, 81, 111, 155 Canadian government regulation, 147–149 Canadian legalization, 150 Cannabis, 151 Career development, 114, 152, 157 management, 83 Christian narratives, 10 Compensation, 152 Competency models, 56–57 Dark side, 72 of personality, 77 recruitment and selection, 155 of talent pools, 51 of TM, 155 Derailment causes, 71, 73, 75–79 gender differences, 80–81 implications for talent management, 71, 73, 82–84 potential behaviours, 75–77 risk, 71, 73, 81 Development, 147 Disappointment, 51–52, 63, 111 Discourse analysis, 130 Disengagement, 63 Durkheim, Emile, 24 Empowering leadership, 91–92, 95–96, 100–102 Exclusive talent, 107–118 management, 107–118 Feminist postructuralism, 129–132 Fourth Industrial Revolution, 34, 53 Gender and derailment, 80–81 Gender identity, 130 Gendered Organization, 129 Giftedness, 15–17 Global Talent Management, 33, 42, 112 Globalisation, 43, 132, 135 God-given talent, 10–11 Golem effect, 111 High performers, 14, 71, 75, 107, 110 High potential (HiPo), 58, 75, 131 employees, 3, 108 for leadership, 1 people, 14 programmes, 58 HRM practices, 13, 89, 92, 107–108, 113, 152 Identity, 7–11 Inclusive organizations, 116 Inclusive talent, 138 management, 107 Individuality, 9–11 Inequalities, 4, 112, 135 Intersectionality, 126, 132–135 Key roles, 153 Knowledge production problem, 39, 41 Leadership, 72, 87–103 derailment, 71–84 failure, 71–73, 76, 78, 81 transitions, 83 Legitimacy, 149–150 Line managers, 14, 16, 63, 87–103 Macro Talent Management (MTM), 43 Macro talent management factors, 147–151 Management practice, 8–10 Managerial ability, 18 Managerial anxiety, 51, 62–64 Managerial capability, 64 Masculinist/masculinisation, 4, 125, 127–131, 133 #Metoo, 126, 133 Micro talent management factors, 151–158 Nine-Box Grid, 19, 57–58 Objectivity, 21, 51–52, 59, 64, 66 Organizational effectiveness, 53, 82 Organizational justice, 107, 111, 119 Performance, 155–156 assessment, 57, 60 ratings, 53, 57–58 Politics, 51–66 Postcolonialism, 125–137 Potential, 1, 3, 16–17, 54–57, 65, 72, 82, 145, 156 individual, 17 Power, 1, 15, 56 Practitioners, 4, 36 Psychometric testing, 58, 67 Pygmalion effect, 20, 114 Rawls, John, 19–20, 24 Recruitment, 153–154 Relevance, of research, 33–44 Reputation, 150–151, 154 Research-practice gap, 36 Retention, 155–157 Return on investment (ROI), 43 Rhetoric of TM, 51–66 Russell, Bertrand, 8 Selection, 154–155 Semantic emptiness, 7, 9 Simonton, Keith, 22–23 Social constructivism, 52, 65 exclusion, 108, 126 inclusion, 108 processes, 52–53, 134 Strategic talent management, 75, 82, 84 Strengths, 76, 79, 88 Subjectivity, 51, 66, 132 Talent, 156–157 actual practices, 54 assessment, 60 attraction, 33, 42, 51, 89, 147, 151–153, 158 deployment, 33, 51 development, 33, 89, 147, 151, 158 as empty signifier, 8–10 engagement, 33 expectations, 24, 61–62, 75, 83 identification, 17–19, 21, 24, 26, 33, 51 innate, 13, 22–23, 25 mobilisation, 100, 102–103 and non-talent identities, 3, 19, 111, 135 nurturing, 51–52 perceived practices, 54 retention, 33, 89, 151, 158 as social construction, 13, 16–21 Talent management assumptions of, 17 employee reactions to, 87–88, 90, 92, 101, 132 employee voice, 132 ethics of, 56, 112 and firm performance, 90 gender blind, 133 managerialist, 1, 125, 132 performativity, 130–131 process, 89 segmentation, 38, 110–111, 132 stakeholders, 3, 38, 41, 45, 87, 107, 147 unitarist, 132 Toxic leadership, 72 Training, 157 Transnationalism, 126, 132–133 Values, 56, 60–61, 75, 82, 111, 113, 117, 119–120, 129, 132, 149, 152 War for talent, 16, 34, 42–43, 109–110, 119, 153 Wittgenstein, Ludwig, 7–8 Workplace inequality, 108 Book Chapters Prelims Introduction Chapter 1: Arbitrariness, Individuality, and the Absence of Work Identity in Talent Management Chapter 2: Social and Natural Constituents of Talent: A Critical Appreciation Chapter 3: Some Critical Reflections on the Relevance of Talent Management Research Chapter 4: The Rhetoric, Politics and Reality of Talent Management: Insider Perspectives Chapter 5: Leadership Derailment: A Neglected Field in Talent Management Chapter 6: The Missing Link: The Role of Line Managers and Leadership in Implementing Talent Management Chapter 7: How Inclusive Can Exclusive Talent Management Be? Chapter 8: Critical Feminist Organisation Studies and Talent Management: Re-imagining Transnational, Intersectional and Postcolonial Agendas Chapter 9: The Paradox of Attracting Key Talent in the Canadian Cannabis Industry: Turning Over a New Leaf 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.112 | 0.491 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".