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Enregistrement W4396972226 · doi:10.1111/bjir.12817

Encyclopedia of human resources management By S.Johnstone, J. K.Rodriguez and A.Wilkinson, London: Edward Elgar. 2023

2024· article· en· W4396972226 sur OpenAlexaff
Diane‐Gabrielle Tremblay

Notice bibliographique

RevueBritish Journal of Industrial Relations · 2024
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueHuman Resource and Talent Management
Établissements canadiensUniversité du Québec
Organismes subventionnairesnon disponible
Mots-clésEncyclopediaRegional scienceSociologyManagementLibrary scienceComputer scienceEconomics

Résumé

récupéré en direct d'OpenAlex

Over recent years, there have been many changes in the labour market, in working conditions, in work organization and in business management. Also, technological changes have been major, artificial intelligence and digitalization being only a few of the phenomena observed. This book is really an encyclopedia, in the sense that it covers many themes with short texts of one page or so, with a few references and cross-references in the book itself, to make it possible to go further on a specific issue. The many changes in the world of work, human resources management, or ‘people’ management as many call it, is questioned and will need to change as well. In such a context of organizational and technological change, this 425-page book offers many insights on the various transformations and their impacts. To our knowledge, this is the first encyclopedia to cover themes that go beyond the field of human resources management, or ‘people’ management per se, to include some terms and expressions that could also be seen more fitting in the areas of sociology of work or labour economics. For example, themes such as work organization, working time, work-life balance, precarious employment, teamwork or telework, to name only a few, are important themes in the sociology of work as well as in human resources management. This book is actually the second and updated edition of the Encyclopedia and includes basic definitions and information on key concepts and terminologies, but also some less known or less familiar aspects of HR terminology, as well as some technical expressions that will be useful for practitioners. Some entries also cover the context of human resources management, including issues such as underemployment, online learning, on-the-job learning, onboarding, part-time work, institutional framework, organizational culture, organizational climate, job security, the 4-day workweek or maternity, paternity and parental leave. In the field of innovation or technology, the most recent changes here are taken into account, with digitalization, platform work, big data, digital work, E-human resources management, E-learning, artificial intelligence as well as artificial intelligence human resources management, giving us a very complete picture of ongoing changes and their impact on work and people. Some new concepts such as Green human resources management are also given some light, while more traditional aspects of RHM or even Industrial Relations such as grievance procedures, fixed-term contracts, pensions, peer appraisal, performance appraisal, performance-related pay, fire and rehire, as well as many others are presented. There are also some elements related to theories, for example Theory X or Y, scientific management, psychometric testing and many others. The book contains very concise entries, but each one of them includes a few references (5−10 or so) in order to indicate further reading which can be useful to better understand the concept. There are over 400 entries relating to human resources management, or ‘people’ management field, indicating the comprehensive nature of the book. It is of course difficult to synthesize an Encyclopedia, but this book definitely merits being on the bookshelves of students and teachers in HRM and social sciences, but also in those of managers, union representatives and all who have an interest in the evolution of the world of work, and the transformation of jobs and work organization. In short, this book is very comprehensive and thoughtful and such a reference resource was clearly missing in the field of HRM or people management.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,166
Score d'incertitude au seuil0,938

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,227
Écart entre enseignants0,213 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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