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

2017· review· en· W2766117791 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

VenueAcademy of Management Proceedings · 2017
Typereview
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSystematic reviewPerformance appraisalHuman resource managementPerformance managementBridge (graph theory)Organizational performanceKnowledge managementPolitical scienceSociologyPsychologyPublic relationsManagementBusinessMEDLINEMedicineComputer scienceMarketing

Abstract

fetched live from OpenAlex

Performance Management (PM), in all its guises, is a core business practice across the majority of organizations; whether this occurs formally through an official organizational process or informally through daily dialogue. Given its inherent importance our aim was to understand how academics have explored PM and therefore we conducted a Systematic Literature Review (SLR) of the scholarly PM literature over a period of more than 11 years, resulting in 219 articles from X different journals. The prevalent themes related to the role of organizational culture, the psychometric properties of Performance Appraisals (PAs) and the linkage of the PM system to other human resource management (HRM) systems; but what we saw was a gap in the scholarly literature as it relates to how we enact PM in practice. Therefore, we conclude with a suggested future research agenda to bridge this research-practice gap, with an emphasis on moving scholarly research from a focus on performance appraisal (or annual performance review) to PM.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.240
GPT teacher head0.494
Teacher spread0.254 · 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