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Record W2893053220 · doi:10.1177/1534484318798533

Performance Management: A Scoping Review of the Literature and an Agenda for Future Research

2018· review· en· W2893053220 on OpenAlexaff
Travor C. Brown, Paula O’Kane, Bishakha Mazumdar, Martin McCracken

Bibliographic record

VenueHuman Resource Development Review · 2018
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsHuman resource managementProcess (computing)Performance appraisalHuman resourcesField (mathematics)Knowledge managementPerformance managementPsychologySociologyPublic relationsPolitical scienceProcess managementManagement scienceManagementBusinessComputer scienceEngineeringMarketing

Abstract

fetched live from OpenAlex

Performance management (PM), in all its guises, occurs across all organizations whether formally through an official organizational process or informally through daily dialogue. Given its inherent importance to the field of Human Resource Development (HRD), we conducted a scoping review of the PM literature over a period of more than 11 years, uncovering 230 articles from 41 different journals. Our review suggests that the PM literature explores the more process driven aspect of PM, namely performance appraisal (PA), as opposed to investigating PM in a truly holistic way. Throughout, we suggest a series of research gaps which, if filled, will help both HRD scholars and practitioners better understand how employee performance can be effectively managed in the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.061
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0230.023
Science and technology studies0.0020.002
Scholarly communication0.0060.008
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.107
GPT teacher head0.394
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations136
Published2018
Admission routes1
Has abstractyes

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