Modular Industry Characteristics and Barriers to its Increased Market Share
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modular and offsite construction reduces project duration and cost by synchronizing offsite and onsite work. Project activities are constructed in a controlled offsite facility to minimize effects of inclement weather and site disruptions, while meeting safety and quality requirements. In recent years, many organizations have conducted questionnaires to study characteristics of modular and offsite construction, such as the Modular Building Institute (MBI), Buildoffsite campaigning organisation in the UK, Canadian Manufactured Housing Institute (CMHI), National Institute of Building Sciences, McGraw-Hill Construction, and Fails Management Institute (FMI). This paper introduces a summary of results for a new questionnaire carried out in collaboration between the Department of Building, Civil and Environmental Engineering (BCEE) at Concordia University, MBI, Niagara Relocatable Buildings, Inc. (NRB) in Canada, and the Nasseri School of Building Science and Engineering at the University of Alberta. This questionnaire focuses on two issues: (1) the characteristics of the modular and offsite construction industry, and (2) detected barriers to the increased market share of this industry. For the latter, effort was made to address five factors emanated from a workshop on äóěChallenges and opportunities for modular construction in Canadaäóť held in Montreal in October 2015 to analyze barriers to growth of modular construction in Canada. Key findings of this questionnaire include requests for use of a separate code of modular construction design, innovative financing and insurance solutions, standards that consider procurement regulations, and lending institutions that partner with financial houses to create special lending programs for modular construction.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it