A Tale of One City: The Ottawa Technology Cluster
Bibliographic record
Abstract
The Ottawa Technology Cluster is distinctive forseveral reasons, including its development in the absence of significantventure capital opportunities and the initial lack of competition among itsfirms in the product market.Although many qualitative studies existregarding this cluster, this research seeks to provide empiricalevidence.Previous research regarding both high technology clusters andthe Ottawa Technology Cluster is reviewed, focusing on topics such as the roleof venture capital investors, the use of angel capital, and the prevalence ofnetworking. Data for this study were collected via questionnaires completed by CEOs ofboth high technology (n=111) and non-technology firms (n=75) listed in theOttawa Business Journal Directory; twelve in-depth case studies werealso completed to collect more thorough qualitative data.The firms werefollowed from 2000 to 2003 to determine firm survival rates. The conclusions suggest that the Ottawa Technology Cluster remains intact asa result of non-financial contributions from informal investors and theirnetworks.Additionally, non-technology firms maintain a greater connectionto other individuals and organizations within the cluster; possibleexplanations of this finding are discussed.As discussed in the casestudies, the challenges to firm survival, as well as the strategies promotingsurvival, are discussed. (AKP)
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 | 0.001 | 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) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".