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Record W1985434338 · doi:10.1111/joop.12078

The interactive effect of team and manager absence on employee absence: A multilevel field study

2014· article· en· W1985434338 on OpenAlexaff
Angus Duff, Mark Podolsky, Michal Biron, Christopher Chan

Bibliographic record

VenueJournal of Occupational and Organizational Psychology · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsYork UniversityTrent University
Fundersnot available
KeywordsPsychologyAttendanceMultilevel modelSocial psychologyField (mathematics)Applied psychology

Abstract

fetched live from OpenAlex

Although it is commonly assumed that manager and team absence levels have a significant impact on an individuals’ absence level, research has yet to simultaneously test the effect of these sources, as well their interactive effect on employee absence behaviour. Using archival attendance records for 955 employees, grouped in 79 teams, and the absence records of their respective managers from a large professional services organization, this study considers absence behaviour through the lens and social learning theory and social information processing theory to suggest that absence norms are socially constructed based on social influences of the absence pattern of one's team and manager. Through the use of hierarchical linear modelling to account for group‐level influences on absence behaviour, findings suggest that team‐level absence exerts a greater influence on employee absence than manager absence and that manager absence exerts a moderating influence on this relationship. Implications for attendance management as well as future research are considered. Practitioner points Team absence behaviour exerts a group‐level influence on employee absence behaviour. Manager absence moderates the team absence effect.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.320
Teacher spread0.306 · 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

Citations34
Published2014
Admission routes1
Has abstractyes

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