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Record W2524561061

Improving measurement plans form multiple dimensions : exercising with balancing multiple dimensions - BMP

2005· article· en· W2524561061 on OpenAlexaff
Luigi Buglione, Alain Abran

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsViewpointsControl (management)Perspective (graphical)Set (abstract data type)Computer scienceProcess managementEarned value managementQuality (philosophy)Risk analysis (engineering)Operations managementProject managementOperations researchEngineeringProject management triangleBusinessSystems engineeringProject charterArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Tracking & Control” activities in software projects are most often based, in industry, on just two dimensions of analysis: time and cost. Most often, ‘tracking & control’ excludes other dimensions (such as quality, risks & impact on society, stakeholders’ viewpoint in a broader sense) taken into account in Performance Management models such as EFQM or the Malcolm Baldridge model. How can balancing those multiple concurrent control mechanisms across several dimensions of analysis be done? Balancing Multiple Perspective (BMPs) is a procedure designed to help project managers choose a set of project indicators from several concurrent viewpoints. This paper also presents the related questionnaire with a list of 14 candidate measures helping to compare the “as-is” situation and to figure out what will be the desired one, including cost figures to be possibly considered in the budget for next projects. .

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score0.799

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 science0.0010.000
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 head0.022
GPT teacher head0.228
Teacher spread0.206 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations8
Published2005
Admission routes1
Has abstractyes

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