Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose To detail the changing nature of retail and service activity in Canada's downtowns and examine the role of business improvement areas (BIAs) in promoting downtown vitality. Design/methodology/approach The research is based on a combination of retail structural analysis and case study research. The structural analysis provides data on transitioning urban demographics and tracks retail and service activity sales change in Canada's major metropolitan downtowns. The case study reports an overview of findings from in‐depth research with the Downtown Yonge BIA. A small number of retail metrics are presented. Findings The paper highlights the significant suburb shift in retail activity across Canada's metropolitan areas and the associated challenges that this has resulted in for the downtown. The role of BIAs are outlined, and examined with reference to operation of the BIA concept within the downtown core of Canada's largest metropolitan market, Toronto. Research limitations/implications The research has been selective in focusing on the Downtown Yonge BIA, the experiences of BIAs across Toronto (and other Canada metropolitan areas) are likely to vary widely. Highlights the need to develop metrics to measure performance and compare BIAs. Practical implications The paper provides an interesting perspective on BIA strategies, with the selected metrics providing BIA managers and urban planners with a set of additional measures to assess BIA performance Originality/value The paper relates BIA planning to the development of performance metrics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it