7 Attracting Knowledge Workers and the Creative City Paradigm: Can We Plan for Talent in Montreal?
Bibliographic record
Abstract
In this chapter, we anticipate some consequences of implementing the creative city paradigm in urban planning practice to attract talent. The paper reports on the results of research on factors influencing the attraction and retention of junior knowledge workers - students in science and technology professions- in Montreal. There are three main sections. First, we define the creative city paradigm based on the most recent literature on the subject. We draw on the creative class thesis to explain that the debate also concerns urban regeneration. Next, we summarize our findings on factors influencing the mobility of junior knowledge workers in Montreal; amenities may not be as important as some think, while job opportunities. seem to dominate mobility decisions. We also differentiate the views of students according to their origin (from Canada, Quebec, Montreat or outside Canada). Third, we discuss the transferability of creative city ideas into urban planning practice and the possible social and economic outcomes of such an approach to city planning.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".