HIRED – Helping Industry Reach Engineers Directly An Initiative of Engagement – for Students and Employers
Bibliographic record
Abstract
In an effort to connect Engineering students with the diverse engineering community in Manitoba, University of Manitoba Engineering Society (UMES) and the faculty have collaborated and organized a regular weekly meeting called HIRED – an acronym for “Helping Industry Reach Engineers Directly”. Industry partners are invited and eager to present to an average of 100 students in attendance on a variety of topics. It’s about sharing information – about companies, career opportunities, industry insights, safety in the workplace, employment and employability skills, networking, and job search success. The benefits to students and industry partners are clear. Students are gaining a better understanding of the opportunities available within their profession and learn first-hand about what employers are looking for in an engineering graduate. Employers have the opportunity to meet their future employees and share with students the importance of professional skills and how to make the most out of their engineering education. These weekly meetings are strategically scheduled every Monday night from 5:30 through the fall and winter academic terms with a meal as part of the deal. It’s a winning combination for the students, employers, profession and the faculty.
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 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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.071 | 0.022 |
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".