Initial metrics and pilot program results for measuring the performance of the Canadian construction industry
Bibliographic record
Abstract
A study has been initiated by the Canadian Construction Innovation Council to support the measurement of the performance of the Canadian construction industry. Metrics have been established to cover aspects of cost, time, scope, quality, safety, innovation, and sustainability. The metrics were piloted with industry partners and applied to institutional building and infrastructure projects. The metrics were selected in recognition of other national and international efforts in benchmarking and with a view of supporting analysis at the project, organization, and industry level. The experience gained through the pilot project indicates that the metrics are reasonably well understood in their definition. While the cost, time, scope, and safety information is readily available, as expected, the information for quality innovation and sustainability is not or requires more detailed in-person interviews of project participants to obtain a complete picture of project performance. The data analysis and presentation conducted to date indicates that a combination of radar charts and box plots works best as a means to communicate results. The result of the study to date is a standard set of metrics, and collection and reporting methods for the performance of the Canadian construction industry that are useful as the basis of a broad benchmarking program.
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 | 0.041 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".