Bibliographic record
Abstract
The inspiration for the project came from watching and reading several news items that identified the skyrocketing costs of insurance and the associated deductibles that multiple condominium corporations were experiencing within the Province of Alberta. Upon further investigation of the issue, it was discovered that the ever-increasing costs of insurance, if left unabated, could have a calamitous effect on a condominium corporation and its stakeholders. The research focused on risk identification that included an Impact component and a Likelihood component used to calculate an overall risk score for each identified hazard to a condominium corporation. This was done by developing a risk matrix that scored Risk Impact versus Likelihood of Occurrence that forms the basis of a Risk Assessment for a condominium corporation. Potential risks were identified through interviews with industry stakeholders that included: the Insurance Bureau of Canada, the Insurance Institute of Alberta, a commercial insurance broker, condominium legal experts, and the Government of Alberta (Service Alberta, Treasury and Finance Board), property management, and a condominium corporation. The findings suggest that all condominium industry stakeholders must proactively work with government to find an equitable solution that addresses the needs of all stakeholders. This needs to be done with some urgency to prevent a looming fiscal crisis within the condominium industry. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled) Faculty Mentor: Chris Hancock Department: Business
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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; 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".