Mapping out Deaf spaces in Montreal - GIS applications to Deaf geography

Transcription

1 Mappig out Deaf spaces i Motreal - GIS applicatios to Deaf geography Cythia Beoît, Philippe Apparicio ad Ae- Marie Ségui Uiversity of Québec (INRS-UCS) Presetatio at the AAG Aual meetig Seattle 2011

2 BACKGROUND DEAF GEOGRAPHY Cotributios of Cultural Geography to Deaf studies (Comat, 2010; Mathews, 2007; Valetie ad Skelto, 2003; ) Cosesus amog authors regardig the importace of Deaf spaces ad Deaf places for Deaf people s idetity buildig (Eickma, 2006; Gulliver, 2008; Lachace, 2007; ) Deaf space: A costructed space ad cetral locus of laguage ad kowledge trasmissio through geeratios. Amog these grouded spaces, there are Deaf school ad Deaf clubs (Lachace, 2007; Comat, 2010; Gulliver, 2008; )

3 BACKGROUND GROUNDED DEAF SPACES : A REVIEW OF THE LITERATURE Exploratio of the origis ad the spread of Deaf cultural idetity ad Deafhood o atioal ad cotietal scales by mappig out Deaf pillars with ArcGis (Eickma, 2006) Deaf spaces as social ad idetity catalyzer for the Deaf (Comat, 2010) Deaf schools as achor poits of the deaf commuities spatial distributio (Comat, 2010) OUR PRESENTATION FOCUSES ON GROUNDED DEAF SPACES ONLY

4 RESEARCH OBJECTIVES AND QUESTIONS OBJECTIVES FOR THIS FIRST STEP OF MY RESEARCH Objectively idetify ad qualify Deaf spaces withi the Motreal Islad territory Compare the spatial distributio of two types of services provided i sig laguage Deaf spaces ad o Deaf spaces RESEARCH QUESTIONS Is there a spatial cocetratio of Deaf spaces ad o Deaf spaces? If so, are their locatio ay differet? Or are they showig specific spatial distributio patters?

5 2. DATA AND METHODS 2.1. STUDY AREA DEMOGRAPHY KM MILLION INHABITANTS - 3,700 INHABITANTS PER KM DEAF DEMOGRAPHY Quebec 750,000 ihabitats with hearig limitatios 500,000 remai uidetified or urecogized 250,000 declared their hearig limitatios 235,000 urecogized by the Quebec Health authority 15,000 deaf people o the Quebec Health Authority s registry? Betwee 1,200 ad 1,500 Deaf people i Motreal

6 2. DATA AND METHODS 2.2. GIS DATASET TYPES OF SERVICES N LEISURE 5 EDUCATION 6 MISCELLANEOUS 6 ORGANIZATION/ASSOCIATION 9 SERVICES 21 TYPES OF SPACES DEAF SPACES 29 NON DEAF SPACES 18 TOTAL 47

7 2. DATA AND METHODS 2.2. METHOD: POINT PATTERN ANALYSIS STANDARD DEVIATIONAL ELLIPSE WONG S INDEX NEAREST NEIGHBOUR INDEX KERNEL DENSITY MAPPING

8 2.2.1 STANDARD DISTANCE AND DIRECTIONAL DISTRIBUTION (STANDARD DEVIATIONAL ELLIPSE) MEAN CENTRE SD ( x mc, y ) mc STANDARD DISTANCE Where, = i i = 1, ( ) 2 x x ( y y ) mc + i i= 1 i= 1 = = umber of poits; x i = 1 x i ad y i = X ad Y coordiates of poit i. y i i mc 2

9 2.2.2 WONG S INDEX E i : Stadard distace ellipse for the group of poits i E j : Stadard distace ellipse for the groupe of poits j Juxtapositio No Juxtapositio 0 1

10 2.2.3 POINT PATTERN ANALYSIS: NEAREST NEIGHBOUR INDEX AVERAGE NEAREST NEIGHBOUR DISTANCE: 1 r i = obs = 1 d i EXCEPTED AVERAGE NEAREST NEIGHBOUR DISTANCE: r exp = R = r 1 2 / A NEAREST NEIGHOUR INDEX: obs r exp Where, = umber of poits; d i = earest eighbour distace for the poit i. A = Surface of the study area (Motreal city)

11 2.2.4 KERNEL DENSITY MAPPING KERNEL DENSITY CALCULATES THE DENSITY OF POINTS PER KM 2 IN A NEIGHBORHOOD AROUND THOSE FEATURE (ONE OR TWO KM FOR EXAMPLE)

12 3. RESULTS : STANDARD DEVIATIONAL ELLIPSE

13 3. RESULTS : WONG S INDEX Juxtapositio No juxtapositio DIFFERENT TYPES OF SERVICES SERVICES ASSOCIATION EDUCATION LEISURE SERVICES EDUCATION LEISURE SERVICES MISCELLANEOUS TYPES OF SPACES DEAF SPACES NON DEAF SPACES 0.734

14 3. RESULTS: NEAREST NEIGHBOUR INDEX AVERAGE NEIGHBOUR INDEX SUMMARY ALL DEAF SPACES NON DEAF SPACES OBSERVED MEAN DISTANCE (M) EXPECTED MEAN DISTANCE (M) NEAREST NEIGHBOUR RATIO Z SCORE P-VALUE

15 3. RESULTS: KERNEL DENSITY MAPPING SIMILARITY DISSIMILARITY

16 4. CONCLUDING REMARKS RESULTS SUMMARY Broader distributio of geeral services i the Motreal Islad A high cocetratio of Deaf spaces, especially leisure i Villeray A high cocetratio of o Deaf spaces i Plateau Mot-Royal Similar spatial distributio patters but differet cocetratios aroud former istitutios LIMITS Small amout of data Absece of private services provided i sig laguage i the dataset Gaps i the services history to eable us to idetify whether it s a Deaf space or ot SUGGESTIONS FOR FURTHER RESEARCHES Combiatio of qualitative ad quatitative approaches to explore differet types of accessibility (spatial, liguistic, acceptability, availability, ) Is the spatial distributio of the Deaf populatio iflueced by the locatio of Deaf spaces or other services? Is there ay spatial mismatch betwee these spaces ad the Deaf populatio?