FOUR CASES FROM SOCIAL SCIENCES AND THEIR IMPLICATIONS TO ENGINEERING DESIGN
Bibliographic record
Abstract
Four cases from social sciences are collected in this paper to illustrate how social sciences are relevant to engineering design. The first case, which originates from psychology, discusses how the representation of a problem would affect the human’s problem-solving skill. This case highlights the need of proper design representation for both innovation and communication. The second case shows how peer pressure would affect a personal judgment on a problem. The result of this case emphasizes the importance of the group environment and human interactions to the performance of a design team. The third and fourth cases are two famous examples respectively taken from two mathematically rigorous theories in economics, namely, game theory and social choice theory. The third case discusses the prisoner’s dilemma in game theory, and it illustrates that rational individual decisions do not necessarily lead to a collective rational decision. This case result suggests the development of a mathematical framework for group decision making in team-based engineering design. The fourth case is concerned with the aggregation of individual preferences towards the agreement on a design decision. While the goodness of design can be evaluated from various aspects and subject to different people’s judgment, how to aggregate these opinions to form a logical design choice is not entirely obvious. The fourth case suggests the development of a logical foundation for choosing a good design based on individual preferences or selections. The selection of these four cases is intended to illuminate some unobvious research results from social sciences and their relevance to engineering design. In turn, it is encouraged to explore the multidisciplinary nature of engineering design research and education by investigating the efforts from social sciences.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".