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Record W2169334608 · doi:10.1177/08863680122098513

People, Competencies and Performance: Clarifying Means and Ends

2001· article· en· W2169334608 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

VenueCompensation & Benefits Review · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsCore competencyPerformance measurementExplanatory powerQuality (philosophy)Core (optical fiber)Power (physics)Knowledge managementPerformance managementProcess managementBusinessPsychologyMarketingComputer science

Abstract

fetched live from OpenAlex

The core problem of every organization is performance. Strategic planning, quality, culture and people are the most persistent themes in the drive to enhance employee performance. The best way to align individual behavior with corporate interests is derived through competencies, the peoplebased tool with the greatest versatility and explanatory power. Performance is defined by measurement and shaped by the promise of rewards. Values, purpose, goals, rewards, competencies and leadership development all are individual parts of the performance system. At minimum, performance systems must address purpose and direction, goals, leadership behavior, assessment and measurement and rewards. This article illustrates the difference between two approaches: focus on performance and showcase competencies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.048
GPT teacher head0.249
Teacher spread0.201 · 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