Bibliographic record
Abstract
Hackathons have become a very popular activity in the software domain. These activities give students a chance to work in teams to address challenging, real-world, software design problems in a fast-paced and time-bound environment. This limited duration has both positives (e.g. students can experience the entire design-build-test process during a 2-day event), and negatives (e.g. students may be “hacking” code together instead of following a more rigorous design process); but if designed well can give students a meaningful design experience which develops their empathy, self-efficacy, and sense of belonging. To date, however, these events have typically stayed within the software domain where the cycles of building and testing can happen very rapidly. This paper describes an extra-curricular activity, co-developed with industry, which provided an opportunity for undergraduate students to design, build, and test solutions to a challenging real-world, mechanical problem sourced from an industry partner. This activity was offered as a pilot to approximately 40 students over a weekend in fall 2023 as part of a larger industry “Innovation Challenge” where the majority of students at the challenge were working on a related software problem from the same industry partner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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".