Using prefabricated wood light-frame in multi-storey and non-residential construction projects: Motivations and barriers of professionals in Quebec
Bibliographic record
Abstract
Despite prefabricated wood light-frame construction’s technical viability and ability to address labor shortages and industry productivity issues, its adoption remains limited. As an alternative to steel and concrete in non-residential buildings of four storeys or less and dwellings of five and six storeys, they represent only 23% and 6% of market shares, respectively. Based on a purposive sample of 40 interviews with diverse construction industry professionals in Quebec (Canada), the representations of prefabricated wood light-frame construction was highlighted. A thematic analysis identified the motivations and barriers to prefabrication adoption and the reasons for these positions more precisely. This work examined whether these perceptions differ significantly according to main professional activity. The findings confirm existing literature while providing deeper insights into motivations and barriers, revealing new viewpoints. Respondents primarily cited expertise as the most critical barriers. Availability of labor, cost, productivity, and construction quality were identified as key motivators, while manufacturing capacity and coordination were perceived with mixed opinions. Analyzing response profiles suggests that different stakeholders generally have similar perceptions. This research will aid in refining policies and strategies to encourage the widespread adoption of prefabricated wood light-frame in construction practices.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".