Bibliographic record
Abstract
A model for location choice of business establishments is presented for the city of Hamilton, Canada. The model is developed with data from the Business Register of Statistics Canada, the Canadian census, and other ancillary geographic information system information that is produced by a private organization called DMTI Spatial. Using the bid–choice theory, the authors estimate multinomial logit models to study and explain the location choice behavior of individual business establishments with fewer than 200 employees for the period 1996 to 1997. Similar analysis is performed for the period 2001 to 2002. Estimation results suggest that commercial business district, highway, and mall proximities; population density; new residential development; and agglomeration economies influence the location decision of business establishments. The results also point to the existence of land use specialization and firm clustering. Using interaction terms in the specification of the location choice utilities is very effective in teasing out the impacts of firm heterogeneity on the location choice decision of individual firms. Finally, the findings from the two periods examined suggest an overall consistency in location choice behavior over time.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".