Activités tertiaires et hiérarchies urbaines : une évaluation de six méthodes d’analyse
Bibliographic record
Abstract
Urban and regional economists are often asked to construct central place models which will properly describe the urban hierarchy (in terms of the service sector) of the region which they are studying. In all such studies, the chief analytical problem is basically one of correctly defining (and measuring) tertiary activity and of correctly weighting the various functions which make up the service sector. In this paper, the authors review six alternative methods for measuring and weighting tertiary functions. The mathematical and conceptual properties of each approach are discussed and evaluated. In the second part of the article, the authors compare the actual results obtained by these alternative methods, using data on the Quebec urban system to test their results. They conclude that no one method is entirely satisfactory, each approach measuring a part of reality. But some methods do nevertheless seem to perform better than others: in this respect, the use of localization coefficient type approach seems generally to give the least biased results.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".