MétaCan
Menu
Back to cohort
Record W2326525252 · doi:10.1017/jmo.2016.8

Persistent innovation and the role of human resource management practices, work organization, and strategy

2016· article· en· W2326525252 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

VenueJournal of Management & Organization · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of GuelphMcMaster University
Fundersnot available
KeywordsBusinessKnowledge managementWork (physics)Human resource managementHuman resourcesProduct (mathematics)Resource (disambiguation)Government (linguistics)New product developmentSet (abstract data type)Product innovationMarketingProcess managementManagementEngineeringComputer scienceEconomics

Abstract

fetched live from OpenAlex

Abstract This study makes a theoretical contribution by taking a persistent characteristics approach to explore the relationship between human resource management practices and innovation outcomes at the workplace-level. Innovators are categorized by the degree to which they are successful at achieving new product/processes and/or improved product/processes outcomes year over year. The human resource management practices explored include the use of highly qualified personnel, and skill-enhancing, motivation-enhancing, and opportunity-enhancing sub-bundles of practices. Further, work organization practices are also explored including integration and collaboration, introduction of organizational changes, and the use of technology. The findings indicate workplaces that set strategic goals related to innovation, that motivate their employees, that create opportunity for their employees to act, and that make greater use of technology tend to be more persistent innovators. These findings can contribute to the development of government policy, which seeks to improve innovation performance outcomes.

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 score0.825
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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