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Performance Management

2009· book-chapter· en· W4254895964 on OpenAlexaff
Gary P. Latham, Lorne M. Sulsky, H. Robson MacDonald

Bibliographic record

VenueOxford University Press eBooks · 2009
Typebook-chapter
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsWilfrid Laurier UniversityUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsCoachingPerformance appraisalSet (abstract data type)Process (computing)Process managementPerformance managementEmployee Performance AppraisalPsychologyComputer scienceOperations managementKnowledge managementEngineeringBusinessManagementMarketingMedicine

Abstract

fetched live from OpenAlex

Abstract A distinguishing feature of performance management relative to performance appraisal is that the former is an ongoing process whereas the latter is done at discrete time intervals (e.g. annually). Ongoing coaching is an integral aspect of performance management. Performance appraisal is the time period in which to summarize the overall progress that an individual or team has made as a result of being coached, and to agree on the new goals that should be set. Common to the performance management/appraisal process are the four following steps. First, desired job performance must be defined. Second, an individual's performance on the job must be observed. Is the person or team's performance excellent, superior, satisfactory, or unacceptable? Third, feedback is provided and specific challenging goals are set as to what the person or team should start doing, stop doing, or be doing differently. Fourth, a decision is made regarding retaining, rewarding, training, transferring, promoting, demoting, or terminating the employmemt of an individual.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.145
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0080.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1450.060

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 head0.039
GPT teacher head0.245
Teacher spread0.205 · 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 designTheoretical or conceptual
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

Citations22
Published2009
Admission routes1
Has abstractyes

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