Urban interrelation and regional patterning in the department of Puno, Southern Peru
Bibliographic record
Abstract
Le département de Puno s'inscrit autour du lac Titicaca (3 800 m au-dessus du niveau de la mer) pour occuper un vaste plateau (l'altiplano) ainsi que les hautes chaînes andines (la puna) et; déborder au nord vers le bassin amazonien (la selva). En utilisant à la fois des informations recueillies lors d'enquêtes sur le terrain et des données de recensement (1940 et 1961), cet essai poursuit un double objectif: on a tenté d'analyser d'une part, l'évolution et l'interdépendance des principaux centres du département de Puno pour proposer, d'autre part, une régionalisation à partir des structures géo-spatiales et des organisations administratives. De plus, on a brièvement traité de la nature des agglomérations et on a réalisé une analyse quantitative regroupant 30 variables reportées sur les 85 districts du département. L'auteur conclut en suggérant que toute planification est un processus qui doit aboutir à un compromis entre des composantes spatio-économiques (planificaciôn tecno-crética) et des composantes socio-culturelles (planificaciôn de base).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".