TIPS & TRAPS:

A LAYMAN’S GUIDE TO USING SHELTER DATA

FOR “HOMELESSNESS” RESEARCH

Harvey LowCity of Toronto

Social Policy & Research Unit

Canadian Conference on Homelessness Toronto, May 2005

1) Homelessness research & Toronto’s Shelter data

2) How research helps address homelessness

3) The “demography” of homelessness

4) Goal: a “TIPS & TRAPS” guide for others exploring the use of shelter data for similar purposes

Purpose of this Presentation

Who are we?

• Social Development & Administration– Strategic policy & research arm– Assists with data & analysis– Works w/ other stakeholders (ex. From Streets to

Homes)

• Shelter Support & Housing, Hostel Services– Service planning & delivery arm– 10 directly-operated shelters– 58 purchase of service

Toronto Administrative Structure2005

Council

City Manager

Auditor

Clerk

Solicitor

CITIZEN FOCUSED SERVICES

Children’s Services

Court Services

Economic Dev. & Culture

Emergency Medical Services

Homes for the Aged

Parks, Forestry, & Recr.

Shelter Support & Housing

Social Services

Public Health

CITIZEN FOCUSED SERVICES

Building

City Planning

Fire Services

Licensing & Standards

Solid Waste

Transportation

Water

INTERNAL SERVICES

Treasurer

Chief Corporate Officer

Accounting

Pension & Payroll

Revenue Services

Purchasing

Corporate Communications

Facilities & Real Estate

Fleet Services

Information & Technology

De puty CityManager &

Chie f Fin anc ialOff icer

De puty CityManager

Deputy CityManager

• Early Challenges:– lack of data– inconsistent data collection– service & administrative data only

1) Homelessness Research & Toronto’s Shelter Data

TIPTIP: Foster relationships with “all” shelter providers. : Foster relationships with “all” shelter providers.

TIPTIP: Develop core set of information. : Develop core set of information.

TIPTIP: Establish data standards. : Establish data standards.

• Collection Challenges:– no consistency in collection (historical consistency)– no process for collection– errors during data capture – recognizing different types of Hostels

TIPTIP: Use a common form (the : Use a common form (the “PINKS”“PINKS”).).

TIPTIP: Establish consistent and uniform times of collection.: Establish consistent and uniform times of collection.

TIPTIP: Develop codes to differentiate hostel type, and avoid estimates & adjustments.: Develop codes to differentiate hostel type, and avoid estimates & adjustments.

• Data Preparation Challenges:– long data “time lag” (time from collection to actual

reporting) – errors during inputting

• Privacy Challenges:– ensuring good data without compromising identity

TIPTIP: Use external data entry (minimize keypunching error).: Use external data entry (minimize keypunching error).

TRAPTRAP: Using internal staff for data entry.: Using internal staff for data entry.

TIPTIP: Document all data assumptions & limitations.: Document all data assumptions & limitations.

TIPTIP: Establish a unique identifiers.: Establish a unique identifiers.

• Semi-Unique ID (initials + birthdate + gender)• Hostel & Hostel Type (derived) • Demographics: Age, Gender, Accompanying Spouse • Family Type (derived)• Number of Dependants• Residence 1 Year Ago• Reason for Service• Admission & Exit Date• Length of Stay (derived)• Reason for Disposition

Toronto’s Core Shelter Data

TRAPTRAP: Collecting : Collecting TOO MUCH DATATOO MUCH DATA!!

• Reporting Challenges:– too technical (audience not kept in mind)!– data not maximized for planning uses – data not put to use for the public good

2) How Research helps address Homelessness

TIPTIP: Use data for BOTH internal and external purposes. : Use data for BOTH internal and external purposes.

TRAPTRAP: Reporting on statistical methods – and not outputs!: Reporting on statistical methods – and not outputs!

• Policy Support:– Mapping & Toronto’s Shelter By-Law– Hadley Inquest

• Internal Planning:– Next Steps Project

• Reporting / Indicators:– Housing & Homelessness Report Cards – Vital Signs– Federation of Canadian Municipalities QOL System

Making the Data/Research RELEVANT

TIPTIP: USE! USE! USE! : USE! USE! USE!

• Positive Collaboration– St. Michael’s Hospital (street deaths)– Status of Women Canada “Young Women &

Homelessness”

Making the Data/Research RELEVANT – cont’d

TRAPTRAP: Doing research for research sake! Not making research : Doing research for research sake! Not making research relevant to the community. relevant to the community.

3) The “Demography” of Homelessness

Total Persons in Toronto Emergency Shelters (1988-2003)

20,000

22,000

24,000

26,000

28,000

30,000

32,000

34,000

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998*

1999*

2000*

2001*

2002*

2003*

Year

Num

ber

* Excludes provincial assaulted women’s shelters.

Total Children in Toronto Emergency Shelters (1988-2003)

2,500

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 * 1999 * 2000 * 2001 * 2002 * 2003 *Year

Num

be

* Excludes provincial assaulted women’s shelters.

TIPTIP: Foster relationships with “all” shelter providers. : Foster relationships with “all” shelter providers.

TIPTIP: Develop core set of information. : Develop core set of information.

TIPTIP: Establish data standards. : Establish data standards.

4) A Users Guide – TIPS & TRAPS

TIPTIP: Establish consistent and uniform times of collection.: Establish consistent and uniform times of collection.

TIPTIP: Use a common form (the : Use a common form (the “PINKS”“PINKS”).).

TIPTIP: Develop codes to differentiate hostel type, and avoid : Develop codes to differentiate hostel type, and avoid estimates & adjustments.estimates & adjustments.

TIPTIP: Establish a unique identifier.: Establish a unique identifier.

4) A Users Guide – TIPS & TRAPS - cont’d

TIPTIP: Use external data entry (minimize keypunching error).: Use external data entry (minimize keypunching error).

TIPTIP: Document all data assumptions & limitations.: Document all data assumptions & limitations.

TIPTIP: Use data for BOTH internal and external purposes. : Use data for BOTH internal and external purposes.

TIPTIP: USE! USE! USE! : USE! USE! USE!

TRAPTRAP: Using internal staff for data entry.: Using internal staff for data entry.

TRAPTRAP: Collecting : Collecting TOO MUCH DATATOO MUCH DATA!!

TRAPTRAP: Reporting on statistical methods – and not outputs!: Reporting on statistical methods – and not outputs! TRAPTRAP: Doing research for research sake! Not making research : Doing research for research sake! Not making research

relevant to the community. relevant to the community.

For more information contact:Harvey LowCity of Toronto

Social Development & Administration Division Social Policy Analysis & Research Unit

416-392-8660hlow@toronto.ca

toronto.ca/demographics