Evolving Approaches to Spillover Research: The Implications of Diverse, Nonwork Encounters
Notice bibliographique
Résumé
As management scholars have attempted to paint a more complete picture of the employee experience, the connection between the work and nonwork domains remains a large part of the conversation. While a vast collection of research focuses exclusively on an employee’s work- specific factors, an ever-increasing body of literature acknowledges that the work and nonwork domains consistently spill over into one another (Edwards & Rothbard, 2000; Greenhaus & Beutell, 1985; Greenhaus & Powell, 2006). The literature has long recognized that these domains can come into conflict with one another while simultaneously enriching each other. Yet, the interplay between personal and professional has become increasingly complicated for the modern employee. Changes in the shape and structure of both the family and work domains have proven that these domains are not as static as once thought (Powell, Greenhaus, Allen, & Johnson, 2019). Instead, employees exist beyond the tight bounds of a single work domain and family domain with a spouse and kids. In response, the study of these domains has attempted to look beyond the common parameters of conflict and enrichment and turn instead to the lived experience of individuals as they traverse between the domains. Indeed, the latest concentrations on specific populations, such as breastfeeding mothers (Gabriel, Volpone, MacGowan, Butts, & Moran, 2020), or on specific activities in the nonwork domain, like exercise (Calderwood, Gabriel, ten Brummelhuis, Rosen, & Rost, 2021; ten Brummelhuis, Calderwood, Rosen, & Gabriel, 2022), inform that the nonwork domain contains a wide range of experiences. Recognizing these changes for employees, our symposium takes new angles to common types of spillover (including leisure activities’ influence on work performance and the crossover effects from partners) while also considering new types of social interactions (such as online dating or participating in team-based leisure activities) that spillover in distinct ways. Through these explorations of spillover, we aim to provide novel examples of how the nonwork domain affects the work domain that better represents the modern workforce. Specifically, the papers in our symposium explore well-being outcomes of dating app usage, in-role and extra-role behavioral outcomes of partner sacrifice, proactivity benefits of hobby job participation, and team learning outcomes of team-based leisure activity participation. “Swiping left or right”: Individual dating app experiences and the influence on work Author: Jinfeng Chen; Purdue U., West Lafayette Author: Kelly Schwind Wilson; Purdue U., West Lafayette Author: Jordan Nielsen; Purdue U. Grateful yet guilty: The emotional and behavioral consequences of receiving daily partner sacrifice Author: Min Yu; Arizona State U. Author: Edward McClain Wellman; Arizona State U. Passion projects outside the 9-5: Exploring expressiveness and the nostalgic impact on work outcomes Author: Katelyn Zipay; Purdue U. Author: Sophie Pychlau; Iowa State U. Leisure as a source of team skill-building: Team impacts of group-based leisure learning Author: Brandon Mathew Fogel; U. of Nebraska, Lincoln Author: Amy Bartels; U. of Nebraska, Lincoln Author: Troy Smith; U. of Nebraska, Lincoln Author: Alexandria Lauren Garcia; U. of Nebraska, Lincoln Author: Wu Wei; Wuhan U.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».