MétaCan
Menu
Back to cohort
Record W1895193951 · doi:10.1111/peps.12046

The Invisible Eye? Electronic Performance Monitoring and Employee Job Performance

2013· article· en· W1895193951 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePersonnel Psychology · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsConcordia University
Fundersnot available
KeywordsSupervisorOrganizational citizenship behaviorPsychologyTask (project management)Job performanceSet (abstract data type)Employee engagementApplied psychologyCounterproductive work behaviorJob satisfactionQuality (philosophy)Social psychologyOrganizational commitmentManagementComputer science

Abstract

fetched live from OpenAlex

To enhance employee performance, many organizations are increasingly using electronic performance monitoring (EPM). The relationship between the frequency of EPM use and employee performance is examined in 2 field studies. In Study 1, which uses a unique longitudinal data set, results reveal that shorter time lags between 2 consecutive employee performance assessments are related to better task performance as indicated by call quality metrics. A second field study using matched supervisor–employee and EPM system data is conducted in 2 call centers to extend these results and to focus more directly on the supervisors’ use of EPM and its relationship with additional performance criteria: counterproductive work behaviors (CWBs) and organizational citizenship behaviors (OCBs). Results indicate that more frequent supervisory use of EPM is associated with better task performance and OCB. However, supervisory use of EPM was not significantly related to CWB.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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