Nonprofit Wage And Equity Survey - Organization-Level Survey Data - FY23 by US Government | Demographics and Population Studies

About this Dataset

Nonprofit Wage And Equity Survey - Organization-Level Survey Data - FY23

A. SUMMARY This dataset is a cleaned and anonymized version of survey data gathered in FY23 from nonprofits who contract with the City and County of San Francisco. Each row is one organization and data includes general information about the nonprofit's services, finances, and operations, and summary demographic data about each nonprofit's workforce. B. HOW THE DATASET IS CREATED This dataset was generated through conducting a two-tiered survey gathering data on organizational characteristics and position-level data from nonprofits who contract with the City and County of San Francisco in FY23. The survey was fielded in October and November of 2022. 152 nonprofits provided organizational-level data and summary data about their workforce. 29 of those organizations (referred to as "Cohort Organizations") provided additional position-level data. This dataset includes organization-level data for the 152 respondent organizations. For further details on survey methodology, please review page 39 of the Nonprofit Wage and Equity Survey report, linked below in "Related Reports." C. UPDATE PROCESS Data is a one-time survey and will not update. D. HOW TO USE THIS DATASET Review code book, attached in the "About this Dataset" section. E. RELATED REPORTS This dataset informs the Nonprofit Wage and Equity Survey Report, released by the Controller's Office in April 2023. Nonprofit Wage and Equity Survey F. RELATED DATASETS This dataset is one of two datasets of survey data from the Nonprofit Wage and Equity Survey (FY23). Position-level data can be viewed on the Open Data Portal. Nonprofit Wage and Equity Survey - Position-Level Cohort Data - FY23
Organization: City of San Francisco
Last updated: 2023-07-01T14:50:51.258062
Tags: nonprofit

Tables

Table 1

@usgov.city_of_san_francisco_nonprofit_wage_and_equity_survey_38bffc3f.table_1

91.48 KB
152 rows
99 columns


CREATE TABLE table_1 (
  "org_id" BIGINT,
  "primeservicearea" VARCHAR,
  "sa_behavioral_health_services" BIGINT,
  "sa_homelessness_and_housing_services" BIGINT,
  "sa_youth_services" BIGINT,
  "sa_workforce_development" BIGINT,
  "sa_medical_care_physical_health_services" BIGINT,
  "sa_veterans_services" BIGINT,
  "sa_senior_services" BIGINT,
  "sa_childcare_early_childhood_services" BIGINT,
  "sa_family_support_services" BIGINT,
  "sa_legal_aid_services" BIGINT,
  "sa_arts_and_cultural_services" BIGINT,
  "sa_economic_community_development" BIGINT,
  "sa_other" VARCHAR,
  "nhood_bernal_heights" BIGINT,
  "nhood_bayview_hunters_point" BIGINT,
  "nhood_castro_upper_market" BIGINT,
  "nhood_chinatown_nob_hill" BIGINT,
  "nhood_excelsior_outer_mission" BIGINT,
  "nhood_glen_park" BIGINT,
  "nhood_golden_gate_park" BIGINT,
  "nhood_haight_ashbury_lone_mountain_usf" BIGINT,
  "nhood_inner_richmond_outer_richmond_lincoln_park_seacliff" BIGINT,
  "nhood_inner_sunset_sunset_parkside" BIGINT,
  "nhood_lakeshore_oceanview_merced_ingleside" BIGINT,
  "nhood_mission" BIGINT,
  "nhood_noe_valley_twin_peaks_west_of_twin_peaks" BIGINT,
  "nhood_pacific_heights_presidio_heights_marina" BIGINT,
  "nhood_portola_visitacion_valley_mclaren_park" BIGINT,
  "nhood_potrero_hill_mission_bay" BIGINT,
  "nhood_presidio" BIGINT,
  "nhood_russian_hill_north_beach" BIGINT,
  "nhood_south_of_market_financial_district_south_beach" BIGINT,
  "nhood_tenderloin" BIGINT,
  "nhood_treasure_island" BIGINT,
  "nhood_western_addition_japantown_hayes_valley" BIGINT,
  "nhood_citywide" BIGINT,
  "dept_dph" BIGINT,
  "dept_hsh" BIGINT,
  "dept_hsa" BIGINT,
  "dept_mohcd" BIGINT,
  "dept_dcyf" BIGINT,
  "dept_dec" BIGINT,
  "dept_oewd" BIGINT,
  "dept_dpw" BIGINT,
  "dept_other" BIGINT,
  "dept_other_det" VARCHAR,
  "orgsize" VARCHAR,
  "pctccsf" DOUBLE,
  "region" VARCHAR,
  "head_count" BIGINT,
  "nbenefits" VARCHAR,
  "nfte" DOUBLE,
  "pctccsffunded" DOUBLE,
  "vacancy" VARCHAR,
  "vacancy_6ms" VARCHAR,
  "wage_under25" DOUBLE,
  "wage_25_40" DOUBLE,
  "wage_40_55" DOUBLE,
  "wage_55" DOUBLE,
  "union" BIGINT,
  "pctgen_aian" DOUBLE,
  "pctgen_asian" DOUBLE,
  "pctgen_black" DOUBLE,
  "pctgen_latino" DOUBLE,
  "pctgen_mena" DOUBLE,
  "pctgen_nhpi" DOUBLE,
  "pctgen_white" DOUBLE,
  "pctgen_other_race" DOUBLE,
  "pctgen_data_not_collected_race" DOUBLE,
  "pctexec_aian" DOUBLE,
  "pctexec_asian" DOUBLE,
  "pctexec_black" DOUBLE,
  "pctexec_latino" DOUBLE,
  "pctexec_mena" DOUBLE,
  "pctexec_nhpi" DOUBLE,
  "pctexec_white" DOUBLE,
  "pctexec_other_race" DOUBLE,
  "pctexec_data_not_collected_race" DOUBLE,
  "pctgen_female" DOUBLE,
  "pctgen_male" DOUBLE,
  "pctgen_nb" DOUBLE,
  "pctgen_trans_female" DOUBLE,
  "pctgen_trans_male" DOUBLE,
  "pctgen_data_not_collected_gender" DOUBLE,
  "pctexec_female" DOUBLE,
  "pctexec_male" DOUBLE,
  "pctexec_nb" DOUBLE,
  "pctexec_trans_female" DOUBLE,
  "pctexec_trans_male" DOUBLE,
  "pctexec_data_not_collected_gender" DOUBLE,
  "pctexec_twomore" DOUBLE,
  "pctgen_data_not_collected_gender_1" DOUBLE,
  "pctgen_twomore" DOUBLE,
  "pctgen_other_gender" DOUBLE,
  "pctexec_other_gender" DOUBLE,
  "data_as_of" VARCHAR,
  "data_loaded_at" VARCHAR
);