Allocation of pre-kindergarten seats in New York City

Ravi Shroff, Richard Dunks, Jeongki Lim, Haozhe Wang, Miguel Castro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider the problem of identifying locations in New York City that are currently underserved with respect to access to pre-Kindergarten programs. We use two public datasets; the spatial distribution of four-year-olds, and the distribution and seating capacities of pre-Kindergarten programs in public schools and community based organizations. We implement a random allocation algorithm to identify and map underserved locations, then see how these locations change as capacity is added in a random fashion. Our model incorporates travel distance, and we measure the sensitivity of our results to variations in this parameter. We provide evidence that as the pre-Kindergarten capacity in our model increases, the effectiveness of this capacity - as measured by the number of unused seats - decreases, to the extent that when the total capacity in the city equals the number of children, almost 20,000 seats remain unused.

Original languageEnglish (US)
Title of host publicationSemantic Cities
Subtitle of host publicationBeyond Open Data to Models, Standards, and Reasoning - Papers Presented at the 28th AAAI Conference on Artificial Intelligence, Technical Report
PublisherAI Access Foundation
Pages36-40
Number of pages5
ISBN (Electronic)9781577356721
StatePublished - 2014
Event28th AAAI Conference on Artificial Intelligence, AAAI 2014 - Quebec City, Canada
Duration: Jul 28 2014 → …

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-14-11

Other

Other28th AAAI Conference on Artificial Intelligence, AAAI 2014
CountryCanada
CityQuebec City
Period7/28/14 → …

ASJC Scopus subject areas

  • Engineering(all)

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