e-Society: A Community Engagement Framework for Construction Projects
Bibliographic record
Abstract
A majority of construction projects often have a significant impact on the surrounding neighbourhoods and the environment at large. In city scale infrastructure projects, this impact can be detrimental to project success. The affected populations often have concerns and more importantly local knowledge relevant to the project. Capturing and integrating this feedback enhances project sustainability. This integration is a feature of smart city initiatives that have increased collaboration between regulatory bodies and project planners. However, the community has not been able to effectively engage in this process. Accordingly there is a need to facilitate two-way communication to promote community involvement beyond the capabilities of a smart city; this will be achieved through e-Society. An e-Society boosts citywide sustainability by contributing to an expanding pool of knowledge. This research investigates the use of semantic and social web technologies and Information and Communication Technologies (ICT) to facilitate public engagement in construction projects. The proposed framework features a core ontological model that is integrated with web-based middleware. It will contribute to the sustainability of construction projects through enhanced two-way communication and enriched public participation.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".