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Record W2088764918 · doi:10.5430/bmr.v2n2p69

The Structure of Human Resources Assessment Process: Conditions for Criteria Formation

2013· article· en· W2088764918 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBusiness and Management Research · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSocio-economic Development and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsHuman resourcesViewpointsProcess (computing)BusinessProcess managementRisk analysis (engineering)Management scienceComputer scienceKnowledge managementPolitical scienceLawEngineering

Abstract

fetched live from OpenAlex

The main aim of the article is to analyze the structure of the process of human resources assessment in identifying the conditions for the formation of assessment criteria. The first part of the paper reviews the development of viewpoints to human resources since the beginning of the 20 th century. The second part of the paper discusses the emerging problems in improving the activity of the Lithuanian public sector in developing the human resources resounding the time requirements that resonate human resources. The authors’ opinion that in getting ready for the process of human resources assessment, in forming the assessment criteria it is not enough to assess the requirements fixed only in laws and in the documents of organizations. The third part of the paper analyzes the methods of human resources’ assessment process.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.492

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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.057
GPT teacher head0.358
Teacher spread0.301 · 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