Series operativas de población municipal: Censos y padrones de España. 1981 - 2001
Bibliographic record
Abstract
El creciente acceso a instrumentos de análisis y previsión pone de manifiesto dificultades operativas en las series de población: insuficiente desagregación antes de 1991 y heterogeneidad territorial por causa de alteración de términos municipales. El artículo presenta métodos para resolver estos prblemas. La desagregación municipal utiliza un algoritmo de doble correspondencia ACR basado en la estructura por cohortes de las series, además de interpolaciones temporales en casos de carencia de estructura por edad. Referente a ka homogeneidad territorial, se documentan las alteraciones de términos municipales. Los nomenclátors permiten estimar las poblaciones anteriores acordes con la nueva base territorial. El resultado es una serie operativa completa 1981 - 2001 de población de derecho por grupos de edad y de sexo de los 1.108 municipios españoles de 2001
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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 | 0.000 | 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 | 0.001 | 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) | 0.007 | 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".