New York Child Learning Institute

This release follows updates to the code used for processing iodide sea-surface observations. Scripts have been added to enable incorporating new data (as it becomes available) into the dataset archived with British Oceanographic Data Centre (BODC). These updates were made following comments from peer-review of the observational iodide sea-surface dataset's data descriptor manuscript. Only the code associated with preparing the current observational dataset and adding new observations should be considered production-ready. This is still subject to change based on editoral decisions following responses to reviewers. This repository also contains code under development for other subsequent projects, such as using the observational sea-surface iodide data for predicted a spatially and temporally resolved global dataset. Please use later releases if these are available. Reference for archived data: Chance R.; Tinel L.; Sherwen T.; Baker A.; Bell T.; Brindle J.; Campos M.L.A.M.; Croot P.; Ducklow H.; He P.; Hoogakker B.; Hopkins F.E.; Hughes C.; Jickells T.; Loades D.; Reyes Macaya D.A.; Mahajan A.S.; Malin G.; Phillips D.P.; Sinha A.K.; Sarkar A.; Roberts I.J.; Roy R.; Song X.; Winklebauer H.A.; Wuttig K.; Yang M.; Zhou P.; Carpenter L.J.(2019). Global sea-surface iodide observations, 1967-2018. British Oceanographic Data Centre - Natural Environment Research Council, UK. doi:10/czhx.

New York City Transit (NYCT) has a comprehensive framework for assessing, managing, and combating subway fare evasion. The automated fare collection system, implemented between 1994 and 1997, features lessons learned from field trials of prototypes specifically designed to limit fare abuse. Subway crime has decreased 68% since 2000, and the annual average subway evasion rate remains low at approximately 1.3%. Today, the transit authority measures fare evasion with independent silent observers who use stratified random sampling techniques and classify passenger entries into 19 categories. Evasion rates peak at 3 p.m., when students are dismissed, but otherwise hover around 0.9% at peak and 1.9% at off-peak hours. Busy times and locations have higher evasions per hour but lower evasions per passenger. More evasions occur in lower-income neighborhoods. Staff presence apparently does not reduce evasions. Results are released to the press on request, which promotes transparency and accountability. As an evasion deterrent, NYCT increased fines from $60 to $100 in 2008. Police issued 68,000 summonses and made 19,000 evasion arrests in 2009. Arrests are a more effective deterrent than summonses; the proportion of arrests versus summonses increased in 2010. Video monitoring equipment is used to identify and apprehend chronic fare abusers, particularly swipers who sell subway entries by abusing unlimited fare media.

Federal civil rights and environmental justice (EJ) mandates require transit agencies to provide service without racial or income discrimination and to ensure meaningful access by individuals with limited English proficiency. EJ research generally focuses on long-range planning and capital investment decision making. However, for operating agencies, equity in scheduling, service planning, and tactical service delivery operations is critical to compliance with Title VI legislation and FTA Circular C4702.1A. In 2009, New York City Transit (NYCT) designed a service reductions package in response to the economic downturn. EJ considerations were integral to its planning. The use of ridership performance criteria for route selection resulted in fewer impacts on routes with heavily minority or low-income populations. Quantitative analysis ensured that protected demographics were not significantly adversely affected by proposed service rationalizations. Route and frequency modifications and service span changes were evaluated with statistical t-tests during programming stages, resulting in proposals sensitive to equity concerns. Operationally, NYCT actively monitors service using U.S. census, survey, and routine agency data. The t-test and the chi-square test explicitly demonstrate racial and income equity in all aspects of agency operations on the basis of service standards and policies. As an example, t-tests compared the observed load factors with published guidelines; no significant differences in service delivery between demographic groups were found.