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Record W3200038958 · doi:10.17705/1jais.00699

When are Social Network Sites Connections with Coworkers Beneficial? The Roles of Age Difference and Preferences for Segmentation between Work and Life

2021· article· en· W3200038958 on OpenAlexaff
Ariane Ollier‐Malaterre

Bibliographic record

VenueJournal of the Association for Information Systems · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsClosenessRespondentFriendshipSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Individuals are increasingly connected with their coworkers on personal and professional social network sites (SNS) (e.g., Facebook), with consequences for workplace relationships. Drawing on SNS research and on social identity and boundary management theory, we surveyed 202 employees and found that coworkers’ friendship acts (e.g., liking, commenting) were positively associated with closeness to coworkers when coworkers were similar in age to or older than the respondent and were positively associated with organizational citizenship behaviors towards coworkers (OCBI) when coworkers were similar in age. Conversely, harmful behaviors from coworkers (e.g., disparaging comments) were negatively associated with closeness when coworkers were older than the respondent, and with OCBI when coworkers were older than the respondent and coworkers’ friendship acts were high. Preferences for work-life segmentation moderated the relationship between coworkers’ friendship acts and OCBI (but not closeness) such that the positive relationship was stronger when the respondent had low (vs. high) preferences for segmentation. We discuss the theoretical and practical implications of this study and propose an agenda for future research.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.229
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2021
Admission routes1
Has abstractyes

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