Computers, cell phones, and social media. How after-hours communication impacts work-life balance and job satisfaction
Notice bibliographique
Résumé
Abstract The purpose of this study was to test for correlation of after-hours work communication on work-life balance and job satisfaction. The correlation results did not conform to the expectations derived from the literature. Thus, we used follow-up qualitative interviews to understand why the study-participants did not experience a reduction in work-life balance or job satisfaction. Results of the correlations showed a weak positive correlation between after-hours communication via computer and cellphone with work-life balance and job satisfaction. Follow-up interviews showed that participants enjoyed the flexibility afforded by after-hours work communication that contributed to positive work satisfaction and greater balance of work and family. Work after-hours was not viewed as added work, but as an opportunity for flexibility, with a greater focus on family. Recent research confirms this development. Findings imply an organizational need for flexibility to further ensure work-life balance and job satisfaction in light of technological advancements. Key Words: After-Hours Communication, Facebook, Computer-Assisted Communication, Working From Home, Work-Life Balance, Job Satisfaction, Flexibility. Authors’ Bio * Arian T. Moore, Ph.D., serves as an adjunct professor for a number of universities teaching leadership and communication courses. She currently teaches the Leadership and Communication course at Ottawa University and Organizational Communication at Indiana Wesleyan University. She is Editor-in-Chief of Bibs & Business Magazine, a magazine providing resources for working mothers on work life balance. She holds a Ph.D. in Organizational Leadership from Regent University. ** Kathleen Patterson, Ph.D. is a Professor and the Director of the Doctor of Strategic Leadership program in the School of Business & Leadership at Regent University, Virginia Beach, Virginia, U.S.A. She is noted as an expert on servant leadership, and coordinates an annual Servant Leadership Research Roundtable in Virginia Beach, and has co-coordinated three Global Servant Leadership Research Roundtables, in the Netherlands, Australia, and Iceland. *** Bruce Winston Ph.D. is a Professor of Business and Leadership with the School of Business and Leadership at Regent University, Virginia Beach, Virginia, U.S.A. He is the Director of Regent’s PhD in Organizational Leadership Program. ****James A. (Andy) Wood, Jr., Ph.D. is an adjunct professor of Organizational Leadership at Regent University, Virginia Beach, Virginia, U.S.A., as well as a professional leadership coach and consultant. He holds a Ph.D. in Organizational Leadership from Regent University. JCMR Journal of Communication and Media Research, Vol. 11, No. 2, October 2019, pp. 1 - 14
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 source (Gemma direct ou Codex distillé), 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 ».