Strategic roadmaps for construction innovation : assessing the state of research
Bibliographic record
Abstract
A strategic planning initiative was undertaken to advance innovation in the Canadian construction industry. A preliminary step in this strategic planning process was to carry out an inventory of the current state of research relating to the construction process that was conducted within Canadian Universities. It was found that this type of current research inventory was not often included in strategic planning initiatives, but has proven to be a valuable contribution to the process. The paper describes the research inventory initiative and briefly summarizes the resulting picture of the construction research landscape in Canada. This methodology involved collecting summaries of over 100 individual research projects, mainly through direct interviews, and deriving a series of research classifications through a clustering analysis of the results. The projects were classified according to the three dimensions of application area, technology, and innovation lifecycle phase forming a framework for analysis (resulting in three distinct roadmaps of current Canadian construction research). Further dimensions of scale, drivers, and time are then added to further assist the ongoing strategic planning process. Two examples of opportunities and activities underway to improve the innovation climate are discussed as they relate to the use of the framework. The scope of the strategic planning process is expanding in scope to include other stakeholders in the process (e.g., industrial research, users of technology). The results are expected to provide an underlying planning, coordination, and dissemination foundation to improve the ability for the research community to contribute to innovation in the Canadian construction industry. Key beneficiaries of this paper are individuals involved in creating and using industry-level strategic plans for construction innovation. The timeframe for the discussed roadmap is 0-2 years.
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 | 0.003 | 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 | 0.001 |
| 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".