LATIDIA · Investigación

Contando en desacuerdo: medición ponderada en dólares, etiquetado selectivo de la máquina y revisión humana presupuestada de lectores de IA en desacuerdo del texto administrativo

arXiv:2611.13215v1 Tipo de anuncio: nuevo Resumen: Estudiamos la medición asistida por IA cuando una etiqueta de texto se aplica a muchos registros administrativos, el objetivo es un total monetario y las lecturas humanas que anclan las máquinas

La noticia

arXiv:2611.13215v1 Announce Type: new Abstract: We study AI-assisted measurement when one text label applies to many administrative records, the target is a monetary total, and the human readings that anchor the machines disagree. The testbed is 121,070 grant-purpose texts from US tax filings (799,675 records, \$126.4B), labelled by a rule-based classifier and three language models, with a designed sample of 651 texts read independently by three people under one codebook. We state exact conditions for a fixed-predictor difference estimator and for a cross-fitted predictor whose folds are assigned to the whole frame before sampling, under Poisson sampling, and assess the implemented fixed-size procedures by simulation: 8 predictors whose own totals