Bibliographic record
Abstract
Sustainable cities rely on architects, engineers and urban planners, professions in the first tier of professional practitioners in the built environment.Few if any urban and building systems designed by them however are "fit-and-forget".They rely on a "fit-and-manage" strategy.Potentially more significant for the longterm performance of these urban systems and individual buildings is the second tier of professions including technologists, technicians, and trades people.This latter group contributes ideas to the design professions, is employed in the construction or retrofit of these designs, and then operates and manages them over many generations.These second tier practitioners are often neglected or given little significance in the broader urban conversation about the future of our cities.They are an essential grouping however not only because of their crucial role in assuring the life cycle success of sustainable designs but as an important, homegrown employment resource for any community or country.The Seneca Sustainability Partnership, at one of Canada's premier post-secondary institutions, is an advocate for this second tier of professions in ensuring that they are educated in the principles of applied urban sustainability.New training materials, consulting opportunities for technologists, research outreach and public participation are attuned to the role of this second tier.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".