Technology in an Institutional Setting: A Case Study at the University of Guelph
Bibliographic record
Abstract
1 Computer use at the University of Guelph is an important aspect of campus life, however, its environmental impacts are often not realized or considered. These impacts are expressed throughout the manufacturing, use and disposal of on-campus computers, and thus require monitoring and an understanding of each stage of a computer’s lifecycle. The computers located in the various laboratories, libraries and faculty/graduate student offices at the University of Guelph consume various quantities of energy, but as a whole are not operating at optimal efficiency. In addition, the disposal of on-campus computers does not occur in the most environmentally sound manner possible, thus resulting in various departments either diverting unwanted units to landfills or storing them for extended periods of time. Both the inefficient use of energy and the manufacturing and disposal of computer systems leads to the generation and release of toxic compounds into the environment. This report identifies the need for the implementation of campus-wide green procurement strategies with respect to computer acquisition, use and disposal, and offers recommendations regarding improvements of the University of Guelph’s current systems. The implementation of these recommendations will aid the University in serving as an example for other institutions, saving money in the long run, and decreasing its overall environmental impacts. 2
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 | 0.000 |
| 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 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".