External Assessment of Engineering Programs
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
This paper reports on an Industry Focus Group Forum, which was held 20 October 2011. The purpose of the forum was to obtain local Industry’s perception and opinions of the strengths and weaknesses of new engineering graduates from the Department of Electrical and Computer Engineering, University of Manitoba at the time they enter the work force. Key strengths of best-in-class engineering employees were identified, such as attitude, knowledge base, creativity, communication, and initiative. While these were the attributes of best-in-class employees, they represented goals to which new graduates should aspire. The industry members also identified weaknesses of new engineering graduates, such as life-long learning, practical aspects, engineering tools, and communication. The strengths and weaknesses were mapped to Canadian Engineering Accreditation Board attributes for validation. The secondary purpose of the forum was to establish a process by which the Faculty can assess their graduates at the time they enter the workforce. The process involved external opinions of the quality of the Faculty’s new graduates.
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 | 0.000 | 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 | 0.000 |
| 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