Notice bibliographique
Résumé
Introduction Scholars started inquiring into the trend of unionization around the early 1900s. John Commons is considered a pioneer who studied unionization trends around the early 1900s and tried to predict patterns of growth and decline of unionization (Ebbinghaus & Visser, 1999). It was furthered by Ashenfelter, John Pencavel, Bain and Elsheikh mainly in the British and US contexts. These scholars for a long time believed that unionization trends followed the business cycles in industry. When the industry flourished, there was a growth in the unionization and vice versa. It has been established beyond doubt that globally, unionization has been on the decline. The debate about the exact year of decline continues but there is a broad consensus amongst scholars of industrial relations that unionization has been on the decline since late 80s around the world (Checchi & Visser, 2005; Ebbinghaus & Visser, 1999; Visser, 2003; Western, 1997). Pattern of union growth and decline was predominantly studied on the basis of the effect of cyclical factors like unemployment and inflation on the unionization along with factors like major disturbances or a catastrophe and real wages (Ashenfelter & Pencavel, 1969; Bain & Elsheikh, 1976). This strand of research on the patterns of growth and decline of unionization has moved since then from UK & US and has been studied in other economies and geographies like Germany, Scandinavian countries and Canada. The scope of the research has expanded to include structural, economic and sociopolitical factors along with cyclical factors. It is also important to note that the trade unions are actors embedded within the social structure (Polanyi, 1957 for embeddedness). While trade unions perform the important function of representing the workers, the geographical context within which they are located leads to some differences (Herod, 2002; 2003). Hence viewing union decline through the lens of labor geography would nuance our understanding. The aim of our paper is to present integrated view of the factors that have led to decline in unionization, established in literature based on geographies. Since there are differences in connotations about unionization and union practices, we first clarify and define the scope of unionization. We present our analysis of the factors that have led to decline in unionization in terms of geographies and specific to some countries namely the USA, Britain, Germany, India, and China. Finally we discuss the implications and future research possibilities. Definition & Scope of Unionization Since there are wide differences in the understanding of unions and their activities, which could lead to different connotations of unions and unionizations in different geographies (Visser, 2006), we present a definition of Union and the scope of the union activities. For the purpose of this paper union has been defined as, an organization of employees which seeks to represent the job interests of its members to employers and in some circumstances to the state, but which is not dominated by either of them (Bain & Price, 1980: 2). Unionization can be defined in terms of union membership, union density, union activities and union power. Union membership is simply a dichotomous variable in the form of yes or no. Union Density is the ratio of unionized workforce to the total workforce. Net union density is the ratio of current unionized workers who are working and total workforce while gross union density is the ratio of unionized workers including retired and unemployed individuals who are drawing unemployment benefits and the total workforce. Union density has been used as a proxy for union power in studies (Addison, Bailey, & Siebert, 2003). Union activities include involvement in activities like strike, collective bargaining and worker representation. Studies however use strike action and collective bargaining settlement as a way of operationalizing union activities. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».