Delineating functional territories from outer space
Bibliographic record
Abstract
The delimitation of functional spatial units or functional territories is an important topic in regional science and economic geography, since the empirical verification of many causal relationships is affected by the size and shape of these areas. This paper proposes a two-step method for the delimitation of functional territories and presents an application for three developing countries: Mexico, Colombia and Chile. The first step of this method uses nighttime satellite images to identify the boundaries of urban continuums (conurbations). When these continuums extend over more than one municipality, we group and redefine them as a new single spatial unit. The second step calculates a dissimilarity index using bidirectional labor-commuting flows between the resulting areas of the first step and then applies a standard clustering procedure to delineate the definitive functional territories. Our results suggest that, using nighttime satellite images, our method can lead to a more accurate definition of functional territories, especially in developing or underdeveloped countries where the official data on labor-commuting flows are often outdated or unreliable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".