Bibliographic record
Abstract
Knowledge, education, reputation, image, partnerships and co-creation are trends of success. The implication of the idea of interconnection of the academic environment with the business environment and public sector, which has been used in the City of Waterloo and the University of Waterloo, is an example of growing value of a territory and the development of innovative (smart) managerial decisions into a practice. The purpose of the paper is to discuss the results of research conducted in Waterloo, Ontario, Canada, which was focused on the growth of competitiveness through the implementation of smart management systems (Triple Helix Model) in the city’s marketing and governance. The method of case study and qualitative research was applied by the implementation of primary and secondary research approaches. Research was conducted over a period of 4 years during post-graduate studies at the University of Waterloo, Canada. Multiple structured and unstructured interviews were conducted with representatives of the university and public and private sectors in the city of Waterloo. During the years 2011 – 2016, additional materials were collected in order to gain a more realistic picture. The City of Waterloo is a leader in innovations in Canada, with a large number of patents, entrepreneurship incubators, and start-ups. The University of Waterloo, situated in the city of Waterloo, has 15 patents per 10,000 residents, which is a rate four times greater than the Canadian average. Primary research results revealed that the municipality of Waterloo is strongly involved in co-operation with universities in the creation of start-up businesses.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".