Improving measurement plans form multiple dimensions : exercising with balancing multiple dimensions - BMP
Bibliographic record
Abstract
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. .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".