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The digital divide in Detroit 261discuss political and social issues. African Americas are less likely than nonblacksto participate in chat rooms. 6 (Note, however, that interactive discussionsand chat-room participation are low-volume activities on the Internet.)Overall, these findings suggest that the Internet may be a means to overcomeracial and residential barriers. Many activities, where racial prejudice orresidential segregation could interfere with access to important information orto the consumer market, do not exhibit significant differences by race or residence.Moreover, African Americans may be using the Internet to overcomebarriers in the labor market. Not only do the majority of African Americanswho use the Internet use it to access information about employment and careeropportunities, but they are much more likely to do so than non-blacks. Ofcourse, African Americans who are excluded from using the Internet do notenjoy these informational advantages.THE EFFECT OF COMPUTER AND INTERNET USE ONSOCIAL INTERACTION ACROSS SPACE AND RACEMost research on Internet use documents positive effects on social interaction,sociability, community participation, and political involvement (for reviews,see Castells, 2001: 118–25; DiMaggio et al., 2004). We consider the impact ofcomputer and Internet usage on two key indicators of social capital: whether arespondent has been in the home of someone of a different neighborhood (orhad them in his or her home) in the past twelve months, and whether a respondenthas been in the home of someone of a different race (or had them in hisor her home) in the same time period. These items are replicated from theSocial Capital Benchmark Survey (2000) “short form.”Neither race nor residence is a significant predictor of either form of socializing,controlling for gender, education, household income, employmentstatus, family structure, and computer and Internet usage (see table 11.5).African Americans are not more or less likely than non-blacks to have been inthe home of someone of a different neighborhood (or to have had them in theirhomes) or to have been in the home of someone of a different race (or to havehad them in their homes). Similarly, Detroiters are not more or less likely thansuburbanites to have been in the home of someone of a different neighborhood(or to have had them in their homes) or to have been in the home of someoneof a different race (or to have had them in their homes). Similarly, gender doesnot have significant effects on inter-neighborhood or inter-racial socializing.Age is a big predictor of both forms of social interaction. The young (ages18–25) are always much more likely than the old (ages 55+) to have engagedin both types of socializing. Those who are middle-aged (ages 26–54) aremuch more likely than the old to have been in the home of someone of another
Table 11.5Logistic coefficients from regression of inter-neighborhood and inter-racial socializing on income, education,age, race, gender, employment status, location, family structure, and computer and Internet usageBeen in the home of someone from a differentneighborhood (or had them in your home) in thepast 12 monthsBeen in the home of someone of a different race(or had them in your home) in the past 12 monthsVariables (1) (2) (3) (4) (5) (6)Income 0.228** 0.205** 0.193* 0.059 0.052 0.051(0.080) (0.080) (0.079) (0.057) (0.057) (0.056)Education 0.368** 0.343* 0.289* 0.199 0.184 + 0.072 +(0.143) (0.144) (0.147) (0.363) (0.095) (0.096)262Youth 1.685* 1.465 + 1.470 + 1.439*** 1.368*** 1.383***(18–25) (0.804) (0.812) (0.807) (0.363) (0.370) (0.364)Middle-aged -0.287 -0.429 -0.416 0.802** 0.748** 0.777**(26-54) (0.419) (0.428) (0.420) (0.272) (0.278) (0.272)African 0.545 0.622 0.604 0.296 0.334 0.314American (0.469) (0.474) (0.470) (0.326) (0.329) (0.327)Gender -0.380 -0.397 -0.415 -0.310 -0.319 -0.312(female) (0.312) (0.313) (0.315) (0.202) (0.202) (0.202)Currently 0.654* 0.669* 0.652 + 0.355 0.374 + 0.363 +employed (0.339) (0.340) (0.341) (0.220) (0.219) (0.220)
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The Network Society
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© Manuel Castells 2004All rights r
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viContentsPART IV SOCIABILITY AND S
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Figures2.1 Technological developmen
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xTables13.4 Physician reports of th
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xiiNotes on contributorsNathaniel B
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xivNotes on contributorsand Browsin
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AcknowledgmentsThis book is the res
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xviiiEditor’s prefaceinteraction
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xxEditor’s prefaceof socio-techni
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1. Informationalism, networks, and
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Informationalism and the network so
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the network society, in a binary mo
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2. Institutional models of the netw
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Silicon Valley and Finland 51PATHS
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Silicon Valley and Finland 53Table
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Silicon Valley and Finland 55the fi
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Silicon Valley and Finland 57There
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Silicon Valley and Finland 59inform
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Silicon Valley and Finland 61that I
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Silicon Valley and Finland 63EBay,
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Silicon Valley and Finland 65produc
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wholly devoted to, or dependent on,
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Silicon Valley and Finland 69The st
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Silicon Valley and Finland 71JOT Au
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Silicon Valley and Finland 73risk i
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Silicon Valley and Finland 75respec
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Silicon Valley and Finland 77esting
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Silicon Valley and Finland 79100090
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Silicon Valley and Finland 81the Fi
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Silicon Valley and Finland 83——
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The Russian network society 85but s
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The Russian network society 87All t
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The Russian network society 89inequ
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The Russian network society 91estim
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The Russian network society 93expre
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The Russian network society 95in st
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The Russian network society 97actio
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4. The Internet in China: technolog
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The Internet in China 101power of t
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The Internet in China 103cially tho
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The Internet in China 1057060504030
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The Internet in China 107(Baum, 199
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The Internet in China 109native-pla
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The Internet in China 111“network
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The Internet in China 113Usually on
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The Internet in China 115lifestyle
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The Internet in China 117To borrow
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The Internet in China 119Cartier, a
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The Internet in China 121Bu, Wei (2
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The Internet in China 123jianguanzh
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5. Reflexive Internet? The Britishe
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Reflexive Internet? The British exp
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PART IIIThe Network Economy
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146 Marshall Van Alstyne and Nathan
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7. Labor in the network society: le
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176 Chris BennerLABOR AND FLEXIBILI
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178 Chris BennerFlexibility in Work
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180 Chris Bennerservices means that
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182 Chris BennerTable 7.2Indicators
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184 Chris BennerThis service is oft
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186 Chris Bennerof human resource a
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188 Chris Benneryears, however, edu
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190 Chris Bennermarket, however, is
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192 Chris BennerFlexible labor mark
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194 Chris BennerAsaravala, Amit (20
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196 Chris BennerLave, Jean and Weng
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8. Time, space, and technology infi
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200 Caitlin Zaloomthe bids and offe
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202 Caitlin Zaloomexchange, the bro
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204 Caitlin Zaloomrecently, the log
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206 Caitlin Zaloomadvantage of the
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208 Caitlin Zaloomletters to form w
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Page 247 and 248: 226 Keith N. Hamptonits ability to
Page 249 and 250: 228 Keith N. Hamptonimmediately app
Page 251 and 252: 230 Keith N. HamptonREFERENCESAngsi
Page 253 and 254: 232 Keith N. HamptonSouthern Califo
Page 255 and 256: 234 Manuel Castells et al.this stud
Page 257 and 258: 236 Manuel Castells et al.On the ot
Page 259 and 260: 238 Manuel Castells et al.friends a
Page 261 and 262: 240 Manuel Castells et al.Table 10.
Page 263 and 264: 242 Manuel Castells et al.way behin
Page 265 and 266: 244 Manuel Castells et al.by radio.
Page 267 and 268: 246 Manuel Castells et al.The six t
Page 269 and 270: 248 Manuel Castells et al.that belo
Page 271 and 272: 250 Wayne E. Baker and Kenneth M. C
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e-health networks and social transf
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14. Narrowing the digital divide: t
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The US community technology movemen
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community issues, access advanced t
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PART VINetworked social movements a
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342 Jeffrey S. JurisFollowing Fredr
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344 Jeffrey S. Jurisactions and cou
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346 Jeffrey S. Juristime. 13 Some h
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348 Jeffrey S. JurisZapatistas were
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350 Jeffrey S. Juriscollectives aga
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352 Jeffrey S. JurisVisibly impassi
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354 Jeffrey S. Juriselements. Colin
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356 Jeffrey S. Jurisorganizations.
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358 Jeffrey S. JurisNOTES1. Moving
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360 Jeffrey S. JurisMRG,’ which w
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362 Jeffrey S. JurisPolanyi, Karl (
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364 Araba Sey and Manuel CastellsIn
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366 Araba Sey and Manuel Castellsre
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368 Araba Sey and Manuel Castellsci
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370 Araba Sey and Manuel Castellssw
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372 Araba Sey and Manuel Castellspa
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374 Araba Sey and Manuel Castellssu
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376 Araba Sey and Manuel Castellsch
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378 Araba Sey and Manuel Castellsso
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380 Araba Sey and Manuel CastellsCo
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PART VIIThe culture of the network
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386 Imma Tubellacultural and sociol
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388 Imma Tubellaand through symboli
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390 Imma TubellaStates. During the
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392 Imma TubellaIn Galicia, autonom
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394 Imma Tubellarooms, including fi
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396 Imma Tubellaunderstand the choi
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398 Imma Tubellainteraction which i
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400 Imma TubellaFerguson, M. (1995)
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18. Globalization, identity, and te
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404 Anshu ChatterjeeIndian entrepre
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406 Anshu ChatterjeeThese enterpris
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408 Anshu Chatterjeerestricted area
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410 Anshu Chatterjeepenetration rat
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412 Anshu Chatterjeeproduced instit
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414 Anshu ChatterjeePunjabi TV face
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416 Anshu Chatterjeedecisions. The
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418 Anshu ChatterjeeNOTES1. For mor
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19. The hacker ethic as the culture
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422 Pekka Himanenthe informational
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424 Pekka Himanenone of the founder
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426 Pekka Himanena work culture in
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428 Pekka Himanenhype in which the
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430 Pekka HimanenWithout renewing t
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Afterword: an historian’s view on
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434 Rosalind Williamsdoes it mean t
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436 Rosalind Williamsindustrial soc
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438 Rosalind Williamsgovernance str
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440 Rosalind Williamsspeech deliver
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442 Rosalind Williamsincarnates as
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444 Rosalind Williamsexponentially
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446 Rosalind Williamsmultiplicity o
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448 Rosalind WilliamsArendt, Hannah
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450 IndexCalifornia, University of:
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452 IndexDetroit Area Study 249, 25
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454 IndexGore, Al 99Gould, Stephen
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456 Indexencryption 71, 76gender ga
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458 IndexMTV 403, 415MTV India 406M
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460 IndexRambler 95Raymond, Eric 35
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462 Indexstatism 15, 17-18, 22, 84,
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464 IndexYahoo! 55, 59, 61Yang, Jer
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