A Domain Model for Requirements-Driven Insight for Internal Stakeholders: A Proposal for an Exploratory Interactive Study
Bibliographic record
Abstract
We propose conducting a 90-minute, interactive exploratory study at EmpiRE'18 that engages attendees in constructing a domain model for requirements-driven insight into system development for internal stakeholders. The domain model is anticipated to enhance internal stakeholders' (e.g., developers, architects, quality manager, etc.) insight into system development from the standpoint of requirements. This should improve: (i) communication among internal stakeholders; (ii) control and management of process and resources for providing requirement-driven insight to stakeholders; and (iii) reuse of the domain model across projects. The study is aimed to generate empirical data to further elaborate and enhance the preliminary model. The participants of the study will be engaged in a model building exercise, and, consequently, have insight into the domain model for internal stake-holders. The revised model will be widely available through subsequent publications. The published model would form a base for further research in the RE community and a guide for practitipractitionersoners in development projects.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Proposal for a workshop study building a requirements-engineering domain model; the object is software development practice, not research practice.
This proposes a requirements-engineering domain model for software stakeholders rather than studying research.
Software requirements-engineering workshop proposal about system-development stakeholders, not scientific research.
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".