Analyzing Internal Stakeholders’ Salience in Product Development
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
Many companies apply Design for X principles to consider production and product lifecycle cost implications in the early phase of product development. In these companies, representatives of different Design for X disciplines form a specific group of internal stakeholders. This single case study constructs a stakeholder salience assessment framework and uses the framework to analyze internal stakeholders’ salience in product development in the case company. As the main result, the compared stakeholders are sequenced and their relative saliences are valued and visualized. In that single case, product management representatives perceived Design for Testing as clearly the most salient stakeholder being four times more salient than Design for Packaging. The framework and assessment procedure are applicable to use in other contexts and companies. This study exemplifies usage of the framework but the results are not generalizable. After salience assessment a company may take corrective actions to increase or decrease the salience of specific stakeholder group, to disband an internal stakeholder group, to consolidate some stakeholder groups together, or to segregate a Design for X group into several groups. The novel approach of this study is to apply the stakeholder salience assessment framework in product development context.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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