Industrialization for sustainable construction
Bibliographic record
Abstract
Sustainable construction (SuCo), which genesis dates in the early 1990’s, advocates the creation and operation of a quality and healthy built environment based on resource efficiency, life cycle economics and ecological principles. (Kibert, 2003). Currently the Construction Industry does not meet all these principles. This implies the need for change, thus innovation for SuCo. The purpose of our study is to explore the opportunities and constraints of a paradigm innovation such as towards industrialised construction to achieve SuCo. The particular issue that is dealt is whether the stakeholders in the CI are indeed willing and ready for a paradigm shift, i.e. a change in the underlying metal models. Have of will they put it into practice by developing and applying industrialised standardized construction technologies. Are there in one way or the other incentives – such as government policies and regulations- that further stimulate such SuCo practices? After all industrialised production in manufacturing sectors has proven to contribute to enhanced efficiency and effectiveness of the processes, thereby minimizing the use of labour and material resources and waste. Thus in the same line of thinking a paradigm shift towards innovative industrialised construction is assumed to contribute to achieve the SuCo objectives. To find answers to the questions the sustainability practices in the construction industry in the Netherlands and Chile were investigated. Methodologically the research drew on a merge of concepts of the Production Management and Innovation Theories. The findings have underpinned that -although the major driving factor for the stakeholders to change the construction processes was cost reduction- the measures to minimize losses in primary materials and material use by industrialised construction which takes into account the environmental aspects contributes to the achievement of the SuCo objectives. The conclusion is that SuCo in the CI requires the implementation of innovative solutions and project execution that goes beyond the traditional and generally accepted way of building. This calls for a paradigm shift amongst construction stakeholders which cannot be accomplished without a stimulating, supporting and regulating framework.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.234 | 0.057 |
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".