Suggestions for Improving Measurement Plans: a BMP application in Italy
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.
Bibliographic record
Abstract
Time and Cost are most often in industry the two main (often solely) dimensions of analysis against which a project is monitored and controlled, excluding other possible dimensions such as Quality, Risks, impact on society and Stakeholders’ viewpoints in a broader sense. Another issue of interest is the proper amount of measures and indicators to implement in an organization to optimizing the tradeoff between the cost of quality and the cost of non quality. How can multiple concurrent control mechanisms across several dimensions of analysis be balanced? The approach of Balancing Multiple Perspectives (BMP) has been designed to help project managers choose a set of project indicators from several concurrent viewpoints. After gathering experiences from Canada, Germany, Turkey and Spain, this paper presents the results from a new BMP application in Italy, using a list of 14 candidate measures interviewing a double set of respondents from academy. Lessons learned are presented, considering the impact that knowledge from universities newbies can bring into ICT organizations.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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 it