“Satisfacción e Informe de Empleo de los Graduados del Red River College de Canadá”
Bibliographic record
Abstract
Canadian higher education institutions continually consider how to improve the quality of the processes and services they offer, thus seeking to increase their contribution to the social and economic development of their environment. In this context, it is taken as a sample of a higher education institution of recognized trajectory in the Canadian province of Manitoba, called Red River College. The tools used to make decisions that allow measuring institutional development, technical cooperation and the satisfaction of their graduates are varied. These are related to a management system implemented by the Federal Government that allows the collection of valid information for decision making. This management system also integrates the job database of the federal government, where the purpose is to offer careers that are demanded by the labor market and to cancel those careers that do not have a job. This system allows universities and the government to have a constant and updated substantive information for the decision making of the actors responsible for higher education that in turn generates a synergy of joint efforts for the benefit of the Canadian population and economy.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".