Timelines of Transportation Infrastructure Delivery 2000 to 2018 in Toronto, Canada and London, UK
Bibliographic record
Abstract
This paper explores the timelines of large transportation infrastructure delivery, from first proposal to construction and opening in London, UK and Toronto, Canada. The goal of the paper is to identify both how long it takes projects to go from idea to delivery, the relative time of different stages in the delivery process, and if projects with long timelines see physical or technological changes in their design. This work contributes to two ongoing discussions around the speed of infrastructure delivery, one that argues infrastructure moves too slowly and major efforts are needed to speed delivery and another that argues that good infrastructure thinking requires time to breathe and care should be taken in rushing through the delivery process. Detailed delivery timelines from initial proposal to construction or operation are developed for 26 transportation projects (16 in Toronto and 10 in London) between the years 2000 and 2018. For each project the timelines of inception, approval, planning, procurement, environmental assessment, construction and operational phases are identified and compared. Long informal gestation periods are identified for many projects, particularly for linear projects. In many instances the informal gestation period dwarfs the time projects spent in formal planning. This research highlights the need to expand the conception of timeliness of infrastructure delivery to include the lengthy periods of informal debate and planning that can span years and build up community expectations about the imminence of a project, even before it has received formal assessment or approval. Detailed delivery timelines from initial proposal to construction or operation are developed for 26 transportation projects (16 in Toronto and 10 in London) between the years 2000 and 2018. For each project the timelines of inception, approval, planning, procurement, environmental assessment, construction and operational phases are identified and compared. Long informal gestational periods are identified for many projects, particularly for linear projects. In many instances the informal gestation period dwarfs the time projects spent in formal planning. This research highlights the need to expand the conception of timeliness of infrastructure delivery to include the lengthy periods of informal debate and planning that can span years and build up community expectations about the imminence of a project, even before it has received formal assessment or approval.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".