A guided evaluation of the impact of research and development partnerships on university, industry, and government
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research and development (R&D) partnerships involve investigative activities that may result in new discoveries and innovations that are critical for the technological advancement of the engineering domain. While demonstrating the value of these partnerships is essential for encouraging investment, the engineering domain lacks a formal evaluation framework. In this paper, a methodology and framework for evaluating R&D partnerships is introduced. The effectiveness of the developed framework is tested using a case study that focuses on the role of the university within the Natural Sciences and Engineering Research Council of Canada Industrial Research Chair program. Using correlation analysis, the activities and investment areas that lead to the desired outcomes for the university research are identified. By using the developed framework over time and applying it to different research programs and industries, key activities and investment areas can be established and improved R&D policies and implementation plans developed.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it