A Survey of Design Reviews: Understanding Differences by Designer-Roles and Phase of Development
Bibliographic record
Abstract
Abstract In this paper, we present the results of a survey of new product development practitioners regarding their design review experiences. We surveyed 128 product development professionals on their experience and preferences in design reviews. We found that the goals and type (location / synchronicity) of design reviews change over the course of a product development project. We found that the majority of design review meetings continue to be held as co-located, live, in-person meetings. For reviewing 3D models, we found that a native CAD package (rather than a viewer, or fixed views, or a physical prototype) is the most commonly used tool. We found a difference between Designers (more likely to be product engineers) and Non-Designers and their access to CAD software, as well as their preference for which tool to use at the design review for 3D model evaluation. We hope that our findings spark future work related to better understanding design reviews and design reviewers in context. Design reviews are an important part of industrial product development processes, so we believe future studies have a large potential to improve these design activities
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How this classification was reachedexpand
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 | 0.046 | 0.245 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".