"Give me your tired, your poor, your huddled masses yearning to breathe free."

1. Vulnerable immigrants, refugees, and population profiles of us urban areas: with particular attention to agents of resettlement and mid-size MSAs Lawrence A. Brown, Tamar E. Mott, Edward J. Malecki Department of Geography Ohio State University A Presentation for the International Geographical Union Congress, Brisbane 2006

2. The Rhetoric of Immigration And An Open Door for Refugees "Give me your tired, your poor, your huddled masses yearning to breathe free."

3. Coming to America…

4. Migration

5. Ellis Island, New York, ca 1900

6. The Mariel Boatlift (1980)

7. 1980 = Economic Migrants = Sent Home mid-1980s = Refugees = Asylum in U.S. Today = Economic Migrants = Sent Home Changing Status: Haitian Boat People

8. Of course, immigration and refugee immigration -- in many respects the bulk of US immigration -- was critical in building our economic machine stimulating cultural change providing an essential labor pool and changing the human geography of the US The US is not alone on these dimensions Refugees may be vulnerable, but they also are valuable

9. Conceptual Context: The Mechanisms of Migration

10. Why do People Move?? Long Standing, Widely Accepted Model is that Migration from an Origin Place O to a Destination Place D is a Function of 1. Job Opportunity Differentials Between O and D 2. Wage Differentials Between O and D 3. Information Flows That Inform Potential Migrants of Conditions + Opportunities in D 4. Origin Push Due to Conditions Such As Famine, Persecution, War Bottom Line -- Things Are Better (Or Thought To Be Better) There than Here Critical Linkages – Earlier Migrants Who Communicate to Potential Migrants Intermediaries / Intermediary Agents Government and NGO Resettlement Agencies Employment or Labor Procurement Agencies

11. How does the model apply in an Immigration Context?? For (virtually) all immigrants -- ◄ Job Opportunity Differentials, Wage Differentials, and/or their equivalent (e.g., freedoms + rights of various sorts) will be (markedly) greater in US ◄Origin Push Factors will apply to (virtually) all ◄Information Flows Factor, therefore, will be instrumental in determining immigrant destinations within US ◄Information Flows include three particular mechanisms – ● Migration Chains whereby current migrants follow earlier migrants ● Distance Decay effects whereby there is less Friction of Distance for origins proximate to US ● Intermediary Actors such as -- Labor Procurement Agents(ies) Government and NGO Resettlement Agents(ies)

12. Most aspects of Conventional Migration Model have been widely studied But, neglected in these efforts are the numerous resettlement programs, which expanded dramatically in half-century since World War II Significant difference: ◄ Migration-chain-type mechanisms, given enormous amount of attention, tend to REPLICATE the settlement patterns of past immigrants ◄ Resettlement programs have the potential to (often) CHANGE those patterns if (i) their foreign-born groups are not represented by earlier immigrants and (ii) MSAs targeted are often non-traditional destinations for immigrants. Four steps: 1. Show differential geographies of immigrant impacts on US urban system 2. Illustrate how programs alter settlement patterns using Office of Refugee Resettlement Data on $$$ allocations to US states 3, Provide specific examples of government and NGO agency (VOLAGS), actions, tying each to Foreign-Born MSA Profiles (I-II-III-IV) identified earlier 4. Using PUMS data for high-refugee nations, relate Government and NGO agency actions to foreign-born MSA profiles (I-II-III-IV)

13. Immigration Largely seen as a bi-coastal phenomena Today, Creeping Inland Rise of New Immigrant Gateways, Latino Growth in Metropolitan America, New Ellis Islands

14. From: Audrey Singer: The Rise of New Immigrant Gateways, Brookings Institution, 2004

15. Immigration Increasingly Impacts Middle America, South, Midwest Areas Not Thought Of as Melting Pots Not the New York-s and Los Angeles-s Areas that Historically Have Been “American” and Caucasian

16. Nevertheless, knowledge of immigration impacts on population profiles of MSAs primarily confined to Los Angeles, New York, Chicago, Miami Research Tasks: ◄ 49 MSAs > 1 million in 2000 Census, largely comprising our “mid-size” ◄ Group to observe MSA profiles in terms of immigrant population ◄ Consider underlying processes that filter immigrants to different MSAs ◄ Focus especially on intermediaries, public and NGO, such as US Immigrant Refugee Resettlement Program (IRR), and Hebrew Immigrant Aid Society (HIAS)

17. MSAs: From Louisville 1.0 million to New York 21.2 million, Distinct break at Philadelphia (6.2 million ), top of our mid-size range. Only San Francisco (7.0 million), Washington (7.6 million), Chicago (9.2 million), Los Angeles (16.4 million), and New York are larger. Variables: Sixteen regions of origin from US Census 2000 – North, West, South, East Europe; East, South Central, Southeast, West Asia; East, Middle, North, South, West Africa; Caribbean; Central and South America Percent MSA Population Foreign Born Standard Grouping Procedures: Principal Components, Group on PC Scores Using SPSS Quick Cluster and Subjective Judgment

19. Table 1: On average 10.6% of population each MSA is foreign-born, but ranges from 2.6% in Cincinnati, Louisville, Pittsburgh to 40.2% Miami. Most dominant region of origin is Central America, primarily Mexicans; 29.1%; ranges from 1.7% in Buffalo to 73.2% San Antonio. Next most important origin is Southeast Asia, dominated by Philippines, also Vietnam; averages 11.2%; ranges from 1.0% Miami to 29.8% Norfolk. East Europe (dominated by Poland, also Russia + Ukraine), East Asia (dominated by China), South Central Asia (dominated by India), Caribbean (dominated by Cuba, Dominican Republic, Jamaica) fall at the 6-8% level; Ranges are for East Europe, from 1.2% in San Antonio to 31.0% in Cleveland; for East Asia, from 0.9% in Miami to 19.1% Seattle; for South Central Asia, from 1.1% in Miami to 13.0% in Cincinnati; for Caribbean, from 0.6% in San Francisco to 55.2% Miami. How does it happen that some MSAs are exceedingly low for many foreign- born groups, e.g., Miami; while broader range of foreign-born groups represented in other MSAs, e.g., Cincinnati (WEur, SCAsia, SAfr), Providence (SEur, WAfr)?

20. Coefficient of Variation, Ratio of Standard Deviation to the Mean. Value < 0.67 (one std dev), indicates wide representation of foreign-born group among MSAs; value > 0.67 indicates clumpiness of representation Only 7 of16 foreign-born groups are below 0.67; 9 above; some egregious Latter include South Europe (1.4), West Asia (1.0), East Africa (1.2), Middle Africa (1.0), West Africa (1.0), Caribbean (1.5) How does it happen that some groups appear only in some places, not others; whereas other groups are more ubiquitous? Basic statistics, then, indicate complexity of the urban geography of the foreign-born and immigration in the US Clearly, there are major differences among MSA profiles in terms of the representation and mix of their foreign-born

21. Resulting Classification Profiles I. Immigration Destinations Since Beginning of the 20th Century, Largely Located in the American Manufacturing Belt -- Target of pre-World War II immigration from Europe, especially Eastern and Southern Europe, and remain so today – Relatively Low Percent Foreign Born Today II. Caribbean + South American Immigrants – 1960s and Later – Very High Percent Foreign Born – Cubans, Dominicans, Haitians – Often Fleeing Poverty, Political Oppression, etc III. Central American, Primarily Mexican, Immigrants – 1960s and Later But With Pre-World II Roots in Migrant Labor Programs (agricultural focus), Industrial Recruitment (steel, meat packing, rr), Wetback crossings – All Among the 26 MSAs with the Largest Mexican Representation IV. South Central and East Asian, African Immigrants Notable – 1980s and Later Immigration – Focus of Resettlement Programs, often major Asian business enterprise and/or strong universities -- Currently Identified as “New Latino Destinations” From: Brown, Mott, Malecki “Immigration Reflections on the Population Profiles of US Urban Areas: Patterns and Processes With Particular Attention to Mid-Size MSAs)

22. I. Immigration Destinations Since the Beginning of the 20th Century, Largely Located in the American Manufacturing Belt -- Target of pre-World War II immigration from Europe, especially Eastern and Southern Europe, and remain so today – Relatively Low Percent Foreign Born Today

23. II. Caribbean and South American Immigrants – 1960s and Later – Very High Percent Foreign Born – Cubans, Dominicans, Haitians – Often Fleeing Poverty, Political Oppression, etc

24. III. Central American, Primarily Mexican, Immigrants – 1960s and Later But With Pre-World II Roots in Migrant Labor Programs (agricultural focus), Industrial Recruitment (steel, meat packing, rr), Wetback crossings – All Among the 26 MSAs with the Largest Mexican Representation

25. IV. South Central and East Asian, African Immigrants Notable – 1980s and Later Immigration – Focus of Resettlement Programs, often major Asian business enterprise and/or strong universities -- Currently Identified as “New Latino Destinations”

26. Composite of All Four MSA Profiles

28. Dimensions That Differentiate These Maps Era of Immigration: Pre World War II, Early 20th Century (I); 1960s and Later (II, III); 1980s and Later (IV) Destination Areas of Immigrants: American Manufacturing Belt (I), Florida (II), West of the Mississippi (Great Plains + West) (III), East of the Mississippi (Mid-West + Southeast (IV) Origin Areas of Immigrants: Europe, especially South and East (I), Caribbean and South America (II), Central America, largely Mexico (III), South Central Asia, East Asia, Africa (IV) Place Characteristics Drawing Immigrants: Industrial Centers (I), Accessibility + Contiguity (II), Accessibility + Contiguity initially w/ Recruitment for Agric + Industry and “Wetbacks” (III), Refugee Resettlement Programs, Foreign Direct Investment, Universities (IV) Foreign Born Profiles of Largest MSAs (> 5 million, except Miami): Chicago, Dallas, Los Angeles, San Francisco – strong Central American, largely Mexican; New York, Miami – strong Caribbean, South American; Boston, Detroit, Philadelphia – Strong European; Washington – strong South Central Asian, East Asian, African

29. Take Away Point – Immigration Patterns are Highly Differentiated Across the Geographic Landscape – Different Places are Impacted Differently – It’s Not Just Immigration, but Immigration of What Type, Immigration By Whom, and Immigration Under What Mechanisms

30. And – An Increasingly New Dynamic The Incredibly Shrinking World!!

31. The Incredible Shrinking World, 1500 to 1960s Global Shrinkage: Effect of Changing Transport Technologies on “Real” Distance Based on McHale (1969), Fig 1

32. The Incredible Shrinking US (1912-1970)

33. →The Model of Migration, The Operant Mechanisms Remains the Same, but →We Have an Incredibly Shrinking World + Political Circumstances, such that →The Substance + Nature Of Immigration Has Changed Over Time, and therefore, →Geographic Landscapes are Impacted Very Differently

34. RECALL -- Classification Profiles I. Immigration Destinations Since Beginning of the 20th Century, Largely Located in the American Manufacturing Belt -- Target of pre-World War II immigration from Europe, especially Eastern and Southern Europe, and remain so today – Relatively Low Percent Foreign Born Today II. Caribbean + South American Immigrants – 1960s and Later – Very High Percent Foreign Born – Cubans, Dominicans, Haitians – Often Fleeing Poverty, Political Oppression, etc III. Central American, Primarily Mexican, Immigrants – 1960s and Later But With Pre-World II Roots in Migrant Labor Programs (agricultural focus), Industrial Recruitment (steel, meat packing, rr), Wetback crossings – All Among the 26 MSAs with the Largest Mexican Representation IV. South Central and East Asian, African Immigrants Notable – 1980s and Later Immigration – Focus of Resettlement Programs, often major Asian business enterprise and/or strong universities -- Currently Identified as “New Latino Destinations”

35. 1. How programs alter settlement patterns Illustrated by Office of Refugee Resettlement (ORR) Data on $$$ allocations to US states

36. Key Measurement Refugee Resettlement Index (RRI) Percent of refugees 1983-2004 for each continental state divided by Percentage of foreign-born for same state in 1980 Similar to familiar location quotient If refugee resettlement mirrored existing settlements of foreign-born, (RRI = 1) latter pattern would be maintained, If refugee resettlement did not follow foreign-born settlement (RRI > 1) pattern of foreign-born settlement altered

37. For Figure 1 Map we also compute Federal Resettlement Allocations by State, averaged over 1997-2005, per Foreign-Born in 2000 Are Federal Resettlement Allocations Proportional or Disproportional to The pattern of the foreign-born??

39. Four RRI categories in Figure 1 -- 1.0 or less indicates state is, at best, matching its FB proportion; 1.75 indicates 75 percent more resettlement than expected by FB level 3.0 indicates 300 percent more; 4.0 indicates 400 percent more Highest impacts on states not traditionally thought of as immigrant destinations – South Dakota (RRI=3.8; $$=53), Georgia (3.8; 15), Kentucky (3.7; 18), Minnesota (3.5; 38), North Dakota (3.0; 136), Missouri (2.8; 33), Iowa (2.8; 31), Washington (2.6, 29) Lowest impact states include ones that are traditional destinations and highly studied – California (RRI=0.9;$$= <10), Texas (0.8; <10), New York (0.7; <10), Illinois (0.6, <10), New Jersey (0.4; <10) Where divergence between RRI and ORR dollars, appears to be result ofsecondary migration by refugees that are more difficult to settle due to language differences and the like Finding:resettlement programs + agencies have significant impact on geography of the foreign-born and redistribution of the Foreign-Born

40. 2. Examples of government and NGO agency (VOLAGS), actions tying each to Foreign-Born MSA Profiles

41. The Inter-Leafing of Migration Patterns -- Late 19th century immigration laid a spatial foundation by which early 20th century immigration was channeled and, in turn, these togetherchanneled migration following World War II -- Foundation was, of course, largely European Mechanisms -- migration chains, established communities, persons/ familieswithin who sponsor immigrants, provide a path for assimilation Facilitators / Intermediaries are a multitude of government, but especially NGO ecumenicalagencies -- who connect(ed) refugees with destinations For many nationalities, then, present-day MSA profiles of foreign-born reflect earlier settlement patterns, as new immigrants and refugees are drawn in by existing communities

42. VOLAGS: Hebrew Immigrant Aid Society (HIAS), founded 1881 American Committee for Christian German Refugees, founded 1934 Catholic Committee for Refugee Victims of Nazi Persecution, 1936 American Fund for Czechoslovak Relief, post-WWII Tolstoy Foundation, post WWII Polish Immigration and Refugee Committe, post WWII American Council for Nationalities Service, 1975 World Relief Organization, 1979 Young Mens Christian Association (YMCA), 1979 Currently, most refugee resettlement in US handled by ten VOLAGS -- Church World Service, Ethiopian Community Development Council, Episcopal Migration Ministries, Hebrew Immigration Aid Society (HIAS), International Rescue Committee, Immigration and Refugee Services of America, Lutheran Immigration on Refugees Services, United States Conference of Catholic Bishops, World Relief Corporation, State of Iowa Bureau of Refugee Services

43. Example: Migration Chains + VOLAGS 1880-1924, 70 pct Slav, Lithuanian, Latvian, Jewish immigrants settled in urban-industrial centers, primarily cities in Profile I -- Boston, Cleveland, Detroit, Philadelphia, Pittsburgh -- New York (Profile II), Chicago (Profile III) -- Largely spontaneous migration, but assisted by Volags Post-WWII, US Displaced Persons Act (1948) and VOLAGS played a major role -- Immigrants from Europe re-settled in existing centers for various nationalities; e.g., Cleveland (Profile I) influx from Poland, Slovenia, Croatia, Hungary. In response to 1956 Hungarian Uprising, refugees were settled in Cleveland + Pittsburgh (Profile I) where Hungarians had moved after suppression of Hungary’s 1848 war of independence.

44. Example: Eastern Europe and VOLAGS -- Pre-World War II Eastern Europeans resettled in Atlantic Coast cities where they disembarked -- New York (Profile II) , Philadelphia (Profile I), Baltimore (Washington MSA, Profile IV) Jewish populations tended to remain in these locales Poles, Hungarians, Czechs often moved to newer cities of industrializing America -- Buffalo (Profile I), Detroit (Profile I), Milwaukee (Profile III), Chicago (Profile III), Cleveland (Profile I); Slovaks, Croatians, Slovenes, Ukrainians favored Pennsylvania Post-WWII, following these established chains, Pittsburgh (Profile I) received Jewish displaced persons; Polish refugees were re-settled with sponsor families in states with large Polish-American communities such as Connecticut, Illinois, Michigan, New Jersey, New York HIAS, in 1999 resettled refugees from former Soviet Union to NYC (Profile II), San Francisco (Profile III), Chicago (Profile III), Los Angeles (Profile III), Philadelphia (Profile I), Boston (Profile I) NB: Eastern Europeans don’t necessarily go to Profile I MSAs (as might be expected) because other Profiles are characterized by more recent immigrants such as Caribbean (II) and Mexicans (III) but retain their strong Eastern Europe base

45. Example: Secondary Migration via Migration Chains 1960s, Cubans already had history in Miami (Profile II). Initially, Cuban refugees were re-settled in Miami/Dade County. Area could not support such heavy increases in population. Federal governmentdirected refugees away from Miami 61 pct of 495,000 Cubans 1961-1981 relocated in, e.g., Chicago, New Orleans, Los Angeles, NYC; Elizabeth, Union City, West New York, other NJ cities. But once Cuban-Americans adjusted to US, learned English, became independent of federal assistance, many relocated back to Miami and other Profile II Florida cities Likewise, resettlement of Hmongs originally directed to scattered communities (e.g., Columbus, Philadelphia, Portland, Seattle, Wausau Wisconsin), but secondary migration led to strong clusters in California (40% of US Hmongs, esp Central Valley + Fresno), Minnesota (26%, esp Minneapolis-St. Paul (Profile IV), Wisconsin (19%, esp Milwaukee (Profile III ).

46. Example: Indochinese US government proposed a “wide dispersal” policy, but VOLAGS that implemented it (beginning about 1975) used their own criteria Operated as autonomous entities and used networks throughout US to findsponsors for refugees. States west of Mississippi received the highest refugee densities, as did the four states where transit camps were located -- California, Pennsylvania, Arkansas, Florida With noIndochinese population base, sponsors tended to be Caucasian and, later, some Chinese Hence, primary settlement narrated by VOLAGS was succeeded by secondary migration, leading to a high level of spatial clustering -- like Cubans and Hmongs

47. Layering or Interleafing Process ● Refugee grouppreceded by earlier migs of same/similar group, migration-chains operate (info flows + sponsorship in US); Example, displaced persons post WWII, mimicked settlement patterns of earlier Eur migs; likewise recent immigs Eastern Europe + former Soviet Union ● Refugee groups have few/no precursors, geographic patterns often altered as agencies target non-traditional immigrant destinations; Example, post-1960s immigrants from Asia, Africa, Caribbean ● Secondary migration might occur, esp among refugeesnot represented by earlier migs, not in culturally-comfortable communities, not near other family or communitymembers; Example, Hmong, Vietnamese, Somalis, and Cubans; Usual mechanisms such as wage/job opp differentials, culture, community, family, and migration chains. Urban Profiles example -- European refugees tended towards Profile I MSAs as expected, but also to Profile II + III MSAs, characterized today by Caribbeans and Latin Americans; Reflects that earlier generations of Europeanswell represented in New York (II) and Chicago (III), but more recent immigrants altered characterization of these MSAs.

48. 3. Using PUMS data for high-refugee nations, relate Government and NGO agency actions to foreign-born MSA profiles (I-II-III-IV)

49. Impactof refugee resettlement programs specifically in terms of 49 MSAs considered, used 2000 PUMS 5% sample to construct Table 3 12 origin countries for which refugee status, and resettlement agencies, have been predominate impetus for migration -- Ukraine, USSR/Russia, Yugoslavia, Cuba, Cambodia, Laos, Vietnam, Eritrea, Ethiopia, Liberia, Somalia, Sudan Using 49 MSAs as base, % of each immigrant group in each MSA is computed; then re-expressed as ratio to the % foreign-born found in that MSA -- produces our Refugee Resettlement Index (RRI) -- similar to familiar location quotient All things being equal, assumption that each MSA’s share of an immigrant group would equal its share of the foreign-born, yielding a value of 1 Ratios above 1 indicate MSA is receiving more of a given groupthanexpected; ratios below 1 indicate receiving less than expected Table 3 highlights cells where RRI is greater than 1.75 and 3.0, indicating that the number of persons from a particular origin is 75% or 300% greater than expected given the number of foreign-born in the MSA

50. NB:RRIs are not solely the result of resettlement efforts; also reflect secondary migration following resettlement which has been common for some groups Examples include Hmongs and Cubans, discussed above in terms of their secondary migration Also Somalis -- Refugee resettlement programs led Somalis to Columbus Ohio (Profile IV) directly, but also considerable secondary migration, triggered by Columbus’ economy and social networks Similarly, Somali refugees have moved in significant numbers from Atlanta (Profile IV) to Portland and Lewiston Maine