Digital Inclusion and Techno-Capital in Austin, Texas

Chris McConnell

Digital Inclusion and Techno-Capital in Austin

RTF Colloquium 25.09.2014

Digital Inclusion❖ The mass adoption of the Internet and other ICTs creates

new opportunities, but also creates new barriers for participation in society.!

❖ Because the ability to make meaningful use of the Internet varies across society, digital inclusion has been a concern for those interested in a just society.!

❖ For this study, specific concerns relate to the ability for individuals to obtain government services, education, and employment.

Divide vs. Inclusion

❖ Internet use is not a binary proposition as “the Digital Divide” framing suggests.!

❖ Livingstone (2007) reframes issue as Digital Inclusion, following from work from Clement and Shade (2000), Warschauer (2004) and others.!

❖ Access to the Internet doesn’t mean people will use it.!

❖ Individuals lie on a spectrum from non-users to expert users.

Deficit Model

❖ Eubanks (2007, 2011) criticizes the “Digital Divide” framing since it works from the presumption that non-users or limited users are somehow personally lacking or failing.!

❖ This deficit model points to individual blame, rather than the broader social conditions that lead to non-use.!

❖ Deficit models also imply that simply addressing deficits eliminates the problem

Material Access❖ Material access is whether an individual has access to an

Internet connection, such as broadband, and the necessary hardware, such as a computer, to go online.!

❖ From the 1990s to the present, material access has been the emphasis of a lot of policy, both in regulation and in interventions such as community technology centers.!

❖ The common “trickle-down” theory (Selwyn, 2004) argues that as computers and Internet become more common, prices will come down, erasing the digital divide.

Skills & Literacies❖ A second and third wave of digital-inclusion research

noted that the ability to use the Internet also presents a barrier to meaningful Internet use. !

❖ Hargittai developed a series of methods to evaluate the skills of individuals, assessing how Internet skills may differ among the population.!

❖ Livingstone extended the concepts of print literacy, computer literacy, and information literacy to Internet use.

van Dijk’s Access Model

❖

Usage Access

Skills Accessstrategic!

informational!instrumental!digital skills

Material Access

Motivational Access

Forms of Capital

❖ Economic Capital!❖ Social Capital!❖ Cultural Capital

❖ Others identified by Bourdieu!

❖ Symbolic Capital!

❖ Technical Capital!

❖ Linguistic Capital!

❖ Informational Capital

Informational Capital

❖ In later work, Bourdieu acknowledges that his concept of cultural capital does not include all of the informational resources members of society may use to exert social power, saying it’s a subset of broader “informational capital.”!

❖ Other types of informational capital may include:!

❖ Linguistic capital!

❖ Bureaucratic capital!

❖ Techno-capital

Dispositions and Habitus

❖ Dispositions are attitudes or perceptions that influence an individual’s behavior.!

❖ Dispositions emerge from experience or the dispositions of others in an individual’s life. !

❖ Habitus is a set of dispositions drawn from life experience.

Applying Bourdieu to Internet Use

❖ Some digital-inclusion researchers have turned to Bourdieu’s notions of capital, disposition, and habitus to better understand barriers to meaningful Internet use. (Brock, Kvasny, & Hales, 2010; Kvasny, 2006a, 2006b; Robinson, 2009, 2011a, 2011b; Rojas et al., 2012; Rojas, Straubhaar, Roychowdhury, & Okur, 2004; Schradie, 2011, 2012; Straubhaar, Tufecki, Rojas, & Spence, 2012)

❖

❖ Some emphasize habitus to understanding barriers and use. (Kvasny, 2006a; Robinson, 2009)!

❖ Others propose a specific type of informational capital relevant to Internet use.

Techno-Capital

❖ Straubhaar (Rojas et al., 2012, 2004; Straubhaar et al., 2012) uses techno-capital to describe the set of resources and tactics an individual can deploy to make meaningful use of the Internet. !

❖ Framing these resources as a form of capital acknowledges the power relationships that are tacit, but perhaps seldom recognized in Internet use. !

!

The Study

❖ Secondary data analysis of existing survey data.!

❖ Applies Bourdieu’s theory of multiple forms of capital and habitus to situate Internet use in its broad social context.!

❖ Describes how Internet use and techno-capital are unequally distributed through society!

❖ Attempts to understand what life experiences contribute to techno-capital

The Survey❖ Mail survey administered in 2010 by City of Austin and

research team lead by Prof. Straubhaar.!

❖ Core sample of 12,000 addresses (households) with an additional 3,000 addresses oversampled in areas identified as low-income or having a high proportion of Hispanic or African-American residents.!

❖ 1,701 surveys were mailed back, for a simple response rate of 11.3%. !

❖ Additional weighting was conducted by Prof. Chen

Research Questions❖ How do the types of access vary among demographic groups in

Austin?!

❖ How do access contexts differ among segments of the population? Which segments are more likely to use the internet in which situations?!

❖ How is techno-capital distributed among demographic groups?!

❖ How does techno-capital differ among individuals with different forms of access?!

❖ Given the complex social context of internet use, what measurable factors affect internet use and techno-capital?

Secondary Data Analysis

❖ Because the survey questionnaire was not designed with these research questions in mind, in come cases, variables were measured indirectly.!

❖ Re-coding variables, such as averaging parents’ educational attainment into cultural capital index!

❖ Constructing indices to approximate social phenomena!

❖ In some cases, data did not describe an important factor in a useful way.

Operationalizing Techno-Capital❖ Respondents rated their comfort with the following tasks on a 1-5 scale:!

❖ Uploading content (ex videos, photos, music) to a website !

❖ Blocking spam or unwanted content!

❖ Adjusting my privacy settings on a website!

❖ Bookmarking a website or adding a website to my list of favorites!

❖ Comparing different sites to verify the accuracy of information!

❖ Creating and managing my personal profile on a social network site!

❖ Creating and managing my own personal website!

❖ These were averaged into an index, with a weighted average of 3.945

Item Averages for Tasks!!

Weighted Mean

Uploading content (ex videos, photos, music) to a website 4.180763

Blocking spam or unwanted content 3.923091

AdjusJng my privacy seLngs on a website 3.953976Bookmarking a website or adding a website to my list of favorites 4.470741

Comparing different sites to verify the accuracy of informaJon 4.013576CreaJng and managing my own personal profile on a social network site 3.985906

CreaJng and managing my own personal website 3.086822

Results on Material Access

❖ 11.88% of Austinites in 2010 said they do not use the Internet at all.!

❖ 65.54% of Austin households had some form of broadband.!

❖ 7.82% of Austinites used the Austin Public Library for Internet access and 7.30% used the city’s free Wi-Fi network.!

❖ Just over half of Austinites, 50.8% used mobile Internet services in some form.

Non-Users by Racial/Ethnic CategoryDo you use the Internet at all?

Racial/Ethnic Category Yes No TotalWhite 95.39% 4.61% 100.00%African-‐American 70.52% 29.48% 100.00%Hispanic 77.11% 22.89% 100.00%Asian-‐American 97.67% 2.33% 100.00%Other 97.25% 2.75% 100.00%

Total 88.12% 11.88% 100.00% Uncorrected chi2(4) = 127.7907

Design-‐based F(2.47, 3447.09)= 8.2906 P = 0.0001

Non-Users by Cultural CapitalDo you use the Internet at all?

Cultural Capital Yes No Total1 74.00% 26.00% 100.00%2 92.23% 7.77% 100.00%3 96.21% 3.79% 100.00%4 96.59% 3.41% 100.00%5 95.38% 4.62% 100.00%


Design-‐based F(2.69, 3574.91)= 6.3510 P = 0.0005

Home Broadband by Racial/Ethnic CategoryHome Broadband ConnecJon

Racial/Ethnic Category no yesWhite 29.42% 70.58% 100.00%African-‐American 59.71% 40.29% 100.00%Hispanic 41.64% 58.36% 100.00%Asian-‐American 16.51% 83.49% 100.00%Other 20.87% 79.13% 100.00%


Design-‐based F(2.71, 3957.96)= 3.3453 P = 0.0222

Home Broadband by Cultural Capital

Home Broadband ConnecJonCultural Capital Index no yes

1 39.37% 60.63% 100.00%2 36.29% 63.71% 100.00%3 24.76% 75.24% 100.00%4 27.32% 72.68% 100.00%5 35.86% 64.14% 100.00%


Design-‐based F(2.14, 2973.25)= 0.9760 P = 0.3814

Results on Techno-Capital

❖ There was frustratingly little variance in Techno-capital, most users scoring between 3 and 4.5.!

❖ Techno-capital generally tracked with cultural capital, education.!

❖ Techno-capital averages were greater among more privileged groups.

Techno-Capital by Race/Ethnicity

Mean Std. Err. 95% Confidence IntervalWhite 4.079874 0.0357148 4.009809 4.149939African-‐American 3.533128 0.1954744 3.149649 3.916607Hispanic 3.757375 0.1348907 3.492748 4.022001Asian-‐American 3.880352 0.3071776 3.277736 4.482969Other 4.515517 0.1132831 4.29328 4.737754Overall Average 3.944982 0.0531121 3.840788 4.049177

F( 4, 1301) = 7.17Prob > F = 0.0000

Techno-Capital by Cultural Capital

Index Mean Std. Err. 95% Confidence Interval1 3.583838 0.1927748 3.205641 3.9620352 3.669506 0.1117195 3.450328 3.8886843 4.133857 0.0756092 3.985522 4.2821924 4.162954 0.0547842 4.055475 4.2704335 4.151816 0.0924264 3.970488 4.333143

Overall Average 3.944982 0.0531121 3.840788 4.049177

F( 1, 1252) = 14.50Prob > F = 0.0001

Techno-Capital by Age

Mean Std. Err. 95% Confidence Interval18-‐24 3.923947 0.1936551 3.544037 4.30385625-‐34 4.286783 0.0762734 4.137151 4.43641435-‐44 4.162311 0.0471695 4.069774 4.25484745-‐54 3.713229 0.0787664 3.558707 3.86775255-‐64 3.479435 0.1395256 3.205716 3.75315465+ 2.87996 0.185548 2.515955 3.243966Overall 3.944982 0.0531121 3.840788 4.049177

F( 5, 1300) = 17.85Prob > F = 0.0000

Place is Important

❖ The place where individuals used the Internet had a statistically significant relationship with techno-capital.!

❖ Using the Internet outside the home had a strong relationship with techno-capital.!

❖ Obviously, to a some extent this is mutually constitutive – people who used the Internet at work may have needed to know how to use the Internet to get the job.

Domestic Use

Domestic Access overall was not statistically significant

Techno-‐Capital Mean Std. Err. 95% Confidence Home Access, 3.860083 0.065809 3.73098 3.989187Does not access at others' homesHome Access, 4.22045 0.131846 3.961797 4.479103accesses at others' homesNo Home Access, 3.291259 0.165005 2.967555 3.614964Accesses at others' homesNo Home Access, 3.513121 0.353771 2.819099 4.207143Does not access at others' homes

F( 3, 1302) = 6.75Prob > F = 0.0002

Institutional Use

Mean Std. Err. 95% Confidence IntervalNo Internet Use at Work or 3.452 0.0801 3.295531 3.609977Uses Internet at Work or School 4.241 0.0397 4.163642 4.319245Overall Average 3.944 0.0531 3.840788 4.049177

F( 1, 1304) = 77.80Prob > F = 0.0000

Institutional Access by Racial/Ethnic Category

InsJtuJonal Internet UseNo Yes Row Total

White 30.53% 69.47% 100.00%African-‐American 68.75% 31.25% 100.00%Hispanic 61.08% 38.92% 100.00%Asian-‐American 25.16% 74.84% 100.00%other 20.71% 79.29% 100.00%

Total 42.24% 57.76% 100.00%

Pearson: Uncorrected chi2(4) = 157.3096

Design-‐based F(2.64, 3855.39)= 8.9699 P = 0.0000

Institutional Access by Cultural Capital

Cultural Capital Index No Yes Row Total1 69.96% 30.04% 100.00%2 52.54% 47.46% 100.00%3 29.81% 70.19% 100.00%4 23.22% 76.78% 100.00%5 18.19% 81.81% 100.00%

Total 40.45% 59.55% 100.00%


Design-‐based F(2.12, 2953.08)= 11.0097 P = 0.0000

Coffee-Shop Use

Techno-‐Capital Mean Std. Err. 95% Confidence

IntervalDoes not use Internet at Coffee Shop 3.837152 0.0632509 3.713067 3.961237

Uses Internet at Coffee 4.277911 0.081009 4.118989 4.436834Overall Average 3.944982 0.0531121 3.840788 4.049177

F( 1, 1304) = 18.39Prob > F = 0.0000

Coffee-Shop Use by Cultural CapitalCultural Capital Index No Yes Row Total

1 91.88% 8.12% 100.00%2 85.34% 14.66% 100.00%3 72.75% 27.25% 100.00%4 70.31% 29.69% 100.00%5 56.46% 43.54% 100.00%

Total 76.70% 23.30% 100.00%

Pearson: Uncorrected chi2(5) = 125.9353 Design-‐based F(3.02, 4411.89)= 7.2251 P = 0.0001

Coffee Shop Use by Race/Ethnicity

No Yes Row TotalWhite 71.12% 28.88% 100.00%

African-‐American 80.34% 19.66% 100.00%Hispanic 90.55% 9.45% 100.00%

Asian-‐American 67.76% 32.24% 100.00%other 90.90% 9.10% 100.00%

Total 77.91% 22.09% 100.00%


Design-‐based F(2.84, 4149.45)= 4.4729 P = 0.0046

Why Institutional Access Matters

❖ Work and School are social spaces where techno-capital may be formed or enhanced.!

❖ Peer support, peer learning, may be at play in school and work contexts!

❖ Lower techno-capital among 18-24 may be indicate techno-capital is formed in office settings or in higher education.!

❖ Use at home appears to have a rather limited relationship with techno-capital.

Logit Model for Non-Users

Number of strata = 1 Number of obs = 1464

Number of PSUs = 1464 PopulaJon size = 1700.1885

Design df = 1463

F(2, 1462) = 15.81

Prob > F = 0.0000

LinearizedCoef. Std. Err. t P>t 95% Confidence

IntervalEducaJon -‐1.177789 0.256106 -‐4.6 0 -‐1.680163-‐0.6754148Age 0.0392188 0.0157483 2.49 0.013 0.0083271 0.0701106_cons -‐0.8759023 1.183453 -‐0.74 0.459 -‐3.197348 1.445543

Cultural Capital EducaJon

African-‐American Hispanic ImmigraJon Age Women

Cultural Capital 1

Significance

EducaJon 0.3787 1

Significance 0

African-‐American -‐0.1016 -‐0.1654 1

Significance 0.0001 0

Hispanic -‐0.23 -‐0.2203 -‐0.0903 1

Significance 0 0 0.0005

Immigrant -‐0.0922 0.0173 -‐0.0215 0.1646 1

Significance 0.0004 0.5097 0.4113 0

Age -‐0.3065 -‐0.0681 0.0761 -‐0.1375 -‐0.0626 1

Significance 0 0.0092 0.0036 0 0.0169

Women -‐0.0084 -‐0.0487 0.0749 -‐0.0114 -‐0.0428 -‐0.0357 1

Significance 0.7474 0.0624 0.0042 0.6631 0.1021 0.172

Regression Model for Techno-Capital

Coef. Std. Err. t P>t 95% Confidence IntervalInsJtuJonal Access 0.3515219 0.0797621 4.41 0 0.1950457 0.507998Mobile Access 0.3090262 0.0631313 4.89 0 0.1851761 0.4328763Women -‐0.2968978 0.0676284 -‐4.39 0 -‐0.4295702 -‐0.1642254Hispanic -‐0.2223119 0.0907368 -‐2.45 0.014 -‐0.4003181 -‐0.0443058Public Access Only 0.1756534 0.0663114 2.65 0.008 0.0455648 0.3057421Home Broadband 0.1719948 0.0738424 2.33 0.02 0.0271318 0.3168578EducaJon 0.0986278 0.0347711 2.84 0.005 0.0304144 0.1668412Age -‐0.0234813 0.0025992 -‐9.03 0 -‐0.0285804 -‐0.0183822Construct 4.229306 0.1673652 25.27 0 3.900971 4.55764

Prob > F = 0.0000 R-‐squared = 0.3853

Broad Conclusions

❖ Material Access is necessary, but not sufficient for meaningful use of the Internet.!

❖ Home broadband, while desirable, may do little to catalyze meaningful use. Simply improving material access does not address significant barriers.!

❖ Institutional access is a likely site of informal learning and peer support.

Conclusions - Policy❖ Using the Internet outside the home in social contexts is important

for developing techno-capital.!

❖ Policy, such as the CoA Digital Inclusion Master Plan, still tends to emphasize material access.!

❖ Material access itself may not be the barrier for many of today’s non-users!

❖ Broaden understanding of digital inclusion beyond material access!

❖ Usability of government websites – often difficult for me to use!!

❖ Prioritize Mobile/Responsive versions of government websites

Conclusions - Further Research

❖ Develop survey items for assessing dispositions!

❖ Investigate how mobile affects cultural capital and to what extent it has been adopted by non-users and users with low techno-capital – 2014 data!

❖ Qualitative inquiry may reveal what happens in environments like work and school to enhance techno-capital and how it might translate to CTCs.