Local Supportive Housing Policy by Continuum of Care
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'A novel and comprehensive cross-sectional dataset (2017) was developed to document and measure municipal supportive housing policy choices and key political factors associated with these choices. The dataset is comprised of 232 municipalities of 354 municipal continuums of care (CoCs) from the HUD 2016 CoC database in order to control for cities directly receiving federal homeless funding. The final sample accounts for 66 percent of all CoCs in the U.S. Municipalities were chosen based on their inclusion in the HUD 2016 Point in Time (PIT) count survey, therefore selecting municipalities with a CoC that are receiving federal funding for homelessness solutions.This is a comprehensive, cross-sectional dataset of municipalities across the United States that includes measures of local homeless policies; measures of local political indic' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Chronic Homeless","cities","Continuum of Care","Local Government","Point in Time Count","Supportive Housing","Urban Politics"]} <|eot_id|>
 Here is the Description of a dataset. Description:'A novel and comprehensive cross-sectional dataset (2017) was developed to document and measure municipal supportive housing policy choices and key political factors associated with these choices. The dataset is comprised of 232 municipalities of 354 municipal continuums of care (CoCs) from the HUD 2016 CoC database in order to control for cities directly receiving federal homeless funding. The final sample accounts for 66 percent of all CoCs in the U.S. Municipalities were chosen based on their inclusion in the HUD 2016 Point in Time (PIT) count survey, therefore selecting municipalities with a CoC that are receiving federal funding for homelessness solutions.This is a comprehensive, cross-sectional dataset of municipalities across the United States that includes measures of local homeless policies; measures of local political indic' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
A novel and comprehensive cross-sectional dataset (2017) was developed to document and measure municipal supportive housing policy choices and key political factors associated with these choices. The dataset is comprised of 232 municipalities of 354 municipal continuums of care (CoCs) from the HUD 2016 CoC database in order to control for cities directly receiving federal homeless funding. The final sample accounts for 66 percent of all CoCs in the U.S. Municipalities were chosen based on their inclusion in the HUD 2016 Point in Time (PIT) count survey, therefore selecting municipalities with a CoC that are receiving federal funding for homelessness solutions.This is a comprehensive, cross-sectional dataset of municipalities across the United States that includes measures of local homeless policies; measures of local political indic
Chronic Homeless; cities; Continuum of Care; Local Government; Point in Time Count; Supportive Housing; Urban Politics