Culture and Shared Understanding in Distributed Requirements Engineering
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
Developing requirements for large software systems requires continuous and effective coordination of tasks, resources, and people. Research in team cognition suggests that the traditional input-process-output model is insufficient for the level of coordination needed in the development of such large systems. Coordination in these projects is greatly affected by human and behavioural factors, relying on developers having a shared understanding of both the system and the project. In globally distributed projects cultural diversity poses interesting challenges to the team's ability to form a shared understanding since developers from different cultures have disparate problem-solving and communication processes. This paper discusses an ongoing study on how culture affects the efforts through which requirements engineers, along with other members of the development team, acquire a shared understanding of both the system requirements and other issues such as project organization and progress. This paper explains the study's theoretical framework and outlines the more specific questions explored
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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 | 0.001 |
| 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