Discussions and Lessons Learned from three iterative and longitudinal studies aiming to optimize the identification and analysis process for stakeholders within a project context
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
Project management research has evolved significantly over the past few decades. Traditionally based on positivism and quantitative approaches, work in the field has gradually expanded to include qualitative interpretative approaches (Biedenbach & Muller, 2011). However, the development of new insights seems to have bypassed several key areas within project management, including stakeholder management. Progress relating to this topic could have a theoretical and pragmatic impact. The work of Achterkamp and Vos (2007) and Jepsen and Eskerod (2009), focusing on stakeholders as a key factor in success, has driven interest in this aspect of project management among academics. The result of this data analysis is that researchers have been able to define several observations and questions with the aim of optimizing the complex process discussed by Bourne and Walker (2006).
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.
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 | 0.004 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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