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Record W4309334159 · doi:10.1016/j.plas.2022.100074

Opening the black box of project team members’ competencies improvement in a public sector organization for a successful transition to the project society

2022· article· en· W4309334159 on OpenAlexaff
France Desjardins, Éric Jean, Christophe Bredillet

Bibliographic record

VenueProject Leadership and Society · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsProject managementContext (archaeology)Knowledge managementProject teamPublic sectorProject management trianglePlan (archaeology)Project charterProcess managementProject planProject stakeholderOPM3BusinessEngineeringComputer sciencePolitical scienceMarketing

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate the project team member's skill developmental activities within the context of a public organization, as to suggest both a theoretical understanding and a procedure adapted for this development, which is based on a reflective approach. The methodology used is based on a qualitative inductive approach subject to a single case study. For an organization with a lightweight project matrix structure to efficiently decentralize the various HR practices related to skill development, the skills evaluation must be self-administered, the development plan and training activities are integrated into the project's lessons learned sessions and support is offered to the project team by an external party (coach). The developmental approach through learning in an occupational environment also enables the organization to adapt to the project society with collaborative and qualified management. This original research stems from its descriptive and comprehensive approach to adapt project management and HRM theories to inform public management.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.148
GPT teacher head0.331
Teacher spread0.183 · 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 designQualitative
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

Citations9
Published2022
Admission routes1
Has abstractyes

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