Arctic Field Projects



Project Title: Social Indicators for Rural Alaska Communities (SIRAC) (Award# 1216399)

PI: Berman, Matthew D (mdberman@alaska.edu)
Phone: (907) 786.5426  
Institute/Department: U of Alaska, Anchorage, Institute of Social and Economic Research 
IPY Project?
Funding Agency: US\Federal\NSF\GEO\OPP\ARC\ASSP
Program Manager: Dr. Anna Kerttula (akerttul@nsf.gov)
Discipline(s): | Data Management | Social and Human Sciences |

Project Web Site(s):
Project: http://anthctoday.org/epicenter/popConference/2016...
NSF_Award_Info: http://www.nsf.gov/awardsearch/showAward?AWD_ID=12...
Data: https://arcticdata.io/

Science Summary:
This project aims to determine how social conditions for Alaska Natives living in small arctic communities have changed since 2000, and differ among communities and small regions. The Census Long Form Survey historically provided much of the data for measuring social and economic conditions in the U.S. Its replacement with the American Community Survey (ACS) after the 2000 Census has raised serious concerns about whether Census data continue to provide accurate measures of well-being in rural Alaska communities, at a time when the region faces unprecedented environmental and socio-economic change. The project addresses the uncertainty with ACS data by developing a new set of social, economic, and cultural indicators with increased capability to detect differences at local scales. Specific objectives include: (1) systematically examine the reliability of ACS data for rural Alaska by disaggregating published margins of error into components expressing dispersion across communities, years, and individuals; (2) construct socio-economic indicators for rural Alaska communities and regions with substantially smaller margins of error than published results; (3) estimate key indicators for communities where observations are sparse or missing entirely; and (4) test whether communities and regions have changed or differ significantly with respect to one or more indicators. The project pursues these objectives through modeling and statistical analyses of multiple primary data sources, including individual interview data from the ACS and the previous censuses in cooperation with the U.S. Census Bureau. Project outputs include a set of socio-economic indicators with improved reliability over published ACS figures that can help state and local governments and non-governmental organizations allocate funds, plan, and evaluate social service and economic development programs. A pioneering application of data assimilation with a social system model aids arctic social observing system design by revealing highest priority targets for new data collection for observing and understanding social change in arctic communities.

Logistics Summary:
The main goal of this project is to determine how social and economic conditions for Alaska Natives living in rural regions of the state have changed since 2000, and differ systematically among communities and small regions. The focus is on indicators collected previously with the Census Long Form Survey and are now reported in the American Community Survey (ACS). To achieve this goal, the project directly addresses the problem of degraded reliability of ACS data at the regional and community level by developing a new set of social, economic, and cultural indicators with increased capability to detect differences for Alaska Native residents. Beginning in 2013, this 5 year project pursues its objectives through three main research tasks involving progressively more complex analyses of primary ACS data and other primary data sources. Creation of confidential data sets at a Census Research Data Center. The starting point for the analysis will be the set of individual and household interview responses from the ACS for the PUMA 400 region of the Alaska: the remote rural portion of the state not connected by road to any urban center. To access ACS microdata, researchers will apply to the U.S. Census Center for Economic Studies Research Data Center (CRDC) program. With approved CRDC access, a team of 2 will then create a dataset that combines all observations for the PUMA 400 region collected by the ACS between 2005 and 2011, adding 2012 when it is released to the CRDC. While the data set will contain responses to all census questions for these populations, the statistical analyses focus on the ACS questions directly related to employment and income, educational attainment, migration, and indigenous language use. The three tasks are: Task 1. Perform analysis of variance with ACS microdata. Task 2. Correlate ACS estimates with data from independent sources. Task 3. Data assimilation with an arctic social system model. No fieldwork is conducted.




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