Geographic differences in the distribution of manufacturing firms in Ontario, Canada
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
For at least the past 20 years, the Province of Ontario – as well as other advanced economic regions – has experienced a period of transition, with traditional manufacturing declining and advanced manufacturing firms and sectors emerging. Concurrently, there has been a concerted policy effort emphasising the development of industry clusters within the province, though key issues of governance and where and how to invest public funds remain. This paper presents research on the spatial configuration of firms in 26 manufacturing sub‐sectors, using point density analysis of the basis for determining the presence and spatial configuration of firms. This allows for the comparison of patterns observed in traditional, advanced, and evolving sub‐sectors. The findings show that there are patterns of clustering in all sub‐sectors, though different spatial configurations are apparent between traditional, advanced, and evolving sub‐sectors. These differences have implications for both investment and governance. Based on the findings, investment needs to be directed towards areas with locational advantages, while regional perspectives and initiatives on cluster governance are needed.
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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 | 0.000 | 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 | 0.000 |
| 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