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Innovative HRM and Organizational Performance

2022· preprint· en· W4312199512 on OpenAlexaff
Scottie Andrew, Ewan Somerville

Bibliographic record

VenuePreprints.org · 2022
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsConestoga College
Fundersnot available
KeywordsHuman resource managementKnowledge managementNothingHuman resourcesCore (optical fiber)ManagementBusinessComputer scienceEpistemologyEconomics

Abstract

fetched live from OpenAlex

This study offers a concise summary of the research that has been done on alternative methods of HRM. A survey of 47 articles on the topic of creative human resource management uncovered three primary schools of thinking. At its core, innovation in HRM entails nothing more than that. One such topic worthy of investigation is the way human resource management approaches new situations. Third, research on inventiveness in the business world has given rise to the concept of "innovative HRM." Each of these three approaches, as well as the theoretical underpinnings of each, will be covered in this article. The note wraps up with a discussion of the significance of the findings for next research as well as clinical practice.

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 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 categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.009
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.077
GPT teacher head0.286
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations1
Published2022
Admission routes1
Has abstractyes

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