The Unbalanced Equation: Technical Opportunities and Social Barriers in the NAE Grand Challenges and Beyond
Bibliographic record
Abstract
The US National Academy of Engineering’s 2008 report, Grand Challenges for Engineering, puts forward a provocative vision of future civilization and engineering’s role in it. Notably, the report signals a trend in engineering toward more explicit and direct engagement with enduring, complex social problems, offering intriguing opportunities for exploring the relationship between engineering and questions of social justice. This paper makes one such exploration by analyzing the report’s explicit framings of engineering-for-social-problem-solving and the implicit assumptions underlying such framings. It shows how the report frames the non-technical factors as external to—and often barriers for—engineering. In contrast, technical challenges, even immense ones, are framed as wholly within engineering’s dominion and as opportunities for both engineering and human civilization as a whole. The paper argues that Grand Challenges signals contemporary tensions in the profession as it seeks an expansive domain of influence and relevance while at the same time narrowly circumscribing what engineers should be accountable for knowing and doing.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.037 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".