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Field and Practice in American High Schools

Field and Practice in American High Schools. James Moody The Ohio State University Population Research Center University of Texas Austin April 23, 2004. Introduction Cause and Consequence in Social Science Put up or shut up: empirically testing an alternative Bourdieu & Field

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Field and Practice in American High Schools

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  1. Field and Practice in American High Schools James Moody The Ohio State University Population Research Center University of Texas Austin April 23, 2004

  2. Introduction • Cause and Consequence in Social Science • Put up or shut up: empirically testing an alternative • Bourdieu & Field • What is a field? • From fields to practice, relations, & risk • Analysis • Data & Measures • How adolescents spend their time • Activity Profiles as “systems of practice” • Global vs. Local perspectives • Case studies of two High Schools • Relational position through blockmodels • Correspondence of Practice & Position • Practice, Position & Youth Risk Behavior • Tentative conclusions • Future (re)directions

  3. Cause and Consequence in Social Science • Standard view: • Science seeks to identify causes of various sorts, with an eye toward manipulation. • The standard requirements for causal inference are (1) isolation, (2) association, and (3) direction (Bollen, 1989). • The most common methods are variations of the general linear model, either singly or in systems of linked equations. • Critiques are common: • Within the standard view there are serious debates about drawing causal conclusions from non-experimental data: Lieberson (1989) Making it Count, Perl Causality; Sobel (1989, 1997, 1996). Concerns basically amount to repeated attempts to better specify either isolation, association, or direction; peppered with concerns for endogeneity and selection. • Outside the standard view, authors argue that treating cause as a system of intersecting forces misrepresents the fundamental actively embedded nature of social life. Abbott has probably been the most visible critic on this front ().

  4. What is a Field? “Field serves as some sort of representation for those overarching social regularities that may also be visualized … as quasi-organisms, systems or structures” J. L. Martin AJS 2003. Bourdieu’s notion of field – particularly as discussed in Language and Symbolic Power – can be thought of as a space of “organized striving” - a “social topology” composed of various “dimensions of capital” that are relevant in a field. This implies two related aspects of a field: (1) the dimensions of capital used to construct the field and (2) the practical guides that generate action in a given activity domain. Examples of fields range from abstract notions of status spaces to concrete examples such as the French academic system.

  5. Field Position Habitus Habitus Everyday Practices Relational Position What is a Field? • Martin identifies 3 basic dimensions of a (socoiological) definition of field: • A topology  a space of/for action, but not simply the distributions of attributes (I.e. not the same as Blau space) • A field of forces  thought of as vectors in the space that act on participants in the field. The analogy here is of magnetic or gravitational fields. • A “battlefield”  a place of active, organized contestation for the resources (usually some sort of status) at play in the field. • We can capture elements of each of these by identifying the relation between position in a social network and the practices that people engage in to signal their position in the field.

  6. Why Look For Fields? • What are some advantages to conceptualizing social spaces as fields, rather than focusing on more ‘normal-science’ explanations for behavior? • Simplification. Field concepts provide a way to undstand systemic activity patterns in large collectives ‘at a distance’. Just as iron filings respond to magnetic fields producing a clear pattern relative to each other, people’s activities (theoretically) admit to regularities that cannot be explained by standard variable-centered approaches. • Embedded Action ontology. Field concepts allow us to move beyond questions about the essence of variables as active agents to notions of people actively navigating community structures. • Relational Focus. Field concepts effectively move the unit of analysis from an individual actor to sets of actors who are positioned relative to each other through social relations and behaviors. • There are also costs. Field concepts are notoriously difficult to specify, causal notions do not follow social science standards for “explaining variance” (but in so doing allows an analysis of constants), and some have argued that they slip uncomfortably toward tautology.

  7. Fields in High School • We’ve known since at least Elmtown's Youth and certainly since The Adolescent Society that schools are significant sites for status struggles. • “Popularity”, the “Leading Crowd” “Thugs”, and so forth all signal positions that carry status implications. • Ethnographic work in schools suggests that youth are actively engaged in exploiting their behaviors and relations to position themselves within this game. • Behaviors, dress, etc. signal a particular position • Adolescents actively manage their social relations for status concerns. • Relations themselves are of key interest to adolescents • The logic of practice in such fields suggest that position in the field should correspond to a relational structure and a distinct pattern of how kids spend their time.

  8. From Field to Practice • Bourdieu seems to suggest that position in a field results in a distinct set of practices that, combined, define relative positions in a given field. These practices are keyed to “everyday” experience, and importantly take place in the real-life constrained time available to participants. • I attempt to operationalize positions of practice by identifying characteristic sets of everyday, time-consuming, activities. • I use (endogenously determined) sets of activities for 2 reasons: • Descriptively, sets might provide a simpler way to characterize ideal types • Behaviorally, I suspect that adolescents collapse others into idealized categories (though they probably have fuzzy boundaries). • The alternative is to measure distance without creating sets. • (Note this might well be contested. Part of the reason I shy away from habitus directly is the link between habitus and dispositions, which (a) are even more difficult to measure than practices and (b) I’m not convinced that actors necessarily are conscious of, and thus able to answer meaningfully about, such dispositions)

  9. Data & Methods • Data: • I use the National Longitudinal Survey of Adolescent Health (Add Health). This is a nationally representative survey of adolescents (7th through 12 grade). My sample consists of students who filled out both the in-school and wave-1 in-home survey. I use the two largest “saturated” schools as case studies. • Methods • Practice Positions are defined using cluster analysis across 17 time-consuming, everyday activities that youth report being involved in. • Global versions situate each student relative to all others in the sample • Local versions identify clusters by comparing people only to those in their own schools • Relational Positions are defined using block models based on regular equivalence • The correspondence of “position and practice” is determined through relational (dyad) models. • The effect of position and practice on risk-related behaviors uses multivariate regression techniques.

  10. Adolescent Activities

  11. Adolescent Activities By Sex

  12. Adolescent Activities By Grade in School To generate activity sets, I cluster over these 17 activity classes. To avoid simply developing markers for gender and age, I standardize all variables within grade and sex

  13. Cluster 1: Low Activity, Church Going, Drivers Cluster 2: Low Activity, Workers Cluster 3: High Activity, Clubs Cluster 4: TV & Video Games Cluster 5: Non-School Active Cluster 6: Church Going, Non-workers Cluster 7: Inactive & Uninvolved Global Cluster Solution 3007 5007 2000 7950 2365 2943 578 901 2413 512 6222 1998 3809 1811 Cluster tree based on a Ward’s minimum variance clustering on 17 variables, standardized by age and sex.

  14. Global Cluster Solution Cluster 1: Low Activity, Church Going, Drivers 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=3007 (21%)

  15. Global Cluster Solution Cluster 2: Low Activity, Workers 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=2000 (14%)

  16. Global Cluster Solution Cluster 3: High Activity, Clubs 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=2943 (21%)

  17. Global Cluster Solution Cluster 4: TV & Video Games 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=901 (6%)

  18. Global Cluster Solution Cluster 5: Non-School Active 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=512 (3.5%)

  19. Global Cluster Solution Cluster 6: Church Going, Non-workers 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=1998 (14%)

  20. Global Cluster Solution Cluster 7: Inactive & Uninvolved 1.5 1 0.5 0 TV Drive Chores Church Cycling Hobbies Exercise Arts_club V.Games Hang Out sport_club HrsWork Active Sport Yth. Grps slife_club PaidWork Acad_club -0.5 -1 -1.5 N=1811 (13%)

  21. Local Practices Case Studies of “Sunshine” & “Jefferson” high schools Center of the school district. Streets and boundaries are educated guesses. Up is not necessarily North.

  22. Local Practices Case Studies of “Sunshine” & “Jefferson” high schools Center of the school district. Streets and boundaries are educated guesses. Up is not necessarily North.

  23. Local Cluster Solution Jefferson High School Cluster 1: Non- Active, Workers 129 324 Cluster 2: Non- School Active 195 488 106 Cluster 3: Non-working, Non Religions 164 58 Cluster 4: Video Gamers 98 Cluster 5: Church Going, School Active 108 10 Cluster tree based on a Ward’s minimum variance clustering on 17 variables, standardized by age and sex.

  24. Local Cluster Solution Jefferson High School Cluster 1 Non-active, Workers 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=129 (22%)

  25. Local Cluster Solution Jefferson High School Cluster 2 Non-School, active 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=195 (33%)

  26. Local Cluster Solution Jefferson High School Cluster 3 Non-workers, non-religious 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=106 (18%)

  27. Local Cluster Solution Jefferson High School Cluster 4 Video Gamers 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=58 (10%)

  28. Local Cluster Solution Jefferson High School Cluster 5 Church Going, School Active 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=108 (18%)

  29. Local Cluster Solution Sunshine High School Cluster 1: Active Non-arts 235 Cluster 2: Non- School, Active 718 277 483 Cluster 3: Inactive & Uninvolved 1064 206 346 Cluster 4: Workers Cluster 5: School Active, Artists 99 Cluster tree based on a Ward’s minimum variance clustering on 17 variables, standardized by age and sex.

  30. Local Cluster Solution Sunshine High School Cluster 1 Active, Non Arts 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=235 (20%)

  31. Local Cluster Solution Sunshine High School Cluster 2 Non-School Active 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=272 (23%)

  32. Local Cluster Solution Sunshine High School Cluster 3 Inactive & Uninvolved 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=206 (18%)

  33. Local Cluster Solution Sunshine High School Cluster 4 Workers 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=346 (30%)

  34. Local Cluster Solution Sunshine High School Cluster 5 School active, Artists 1.5 1 0.5 0 TV arts drive Sport Work Cycle sports Chores std_life Church Friends Hobbies hrswork Exercise videogames Youthgrps acad_club -0.5 -1 -1.5 N=91 (8%)

  35. Comparing Local to Global The overlap between local and global assignments is statistically significant (adjusted rand of about 15%), but the results suggest a fair amount of room for local variation on the global theme. This suggests that, while there are some similarities, social relations might admit to patterning via a local embeddedness or a global identity.

  36. Network Structure • Bourdieu’s discussion of relational fields suggests that position in the field’s status structure will correspond to the development of unique habitus, and thus distinct practices. This leaves open (at least) two possible ways to operationalize position in the field. • Position as regular equivalence. • If position relates to a generalized notion of status, then two actors with similar patterns of relations in the network should have similar behavior profiles. The mechanism here suggests aligning status interests and mimicry between those in “analogous” positions in the field. • Position as direct connection between actors. • If one learns the relevant action rules through direct interaction with others in the field, then those people who are directly connected should have the most similar behavior profiles. The mechanism here is largely one of communication, peer influence & selection.

  37. Network Structure Regular Equivalence through triad distributions (0) (1) (2) (3) (4) (5) (6) 003 012 102 111D 201 210 300 021D 111U 120D Intransitive Transitive 021U 030T 120U Mixed 021C 030C 120C

  38. 120D_S 003 021C_S 120D_E 021C_B 012_S 021C_E 120U_S 012_E 120U_E 111D_S 012_I 120C_S 111D_B 102_D 120C_B 111D_E 102_I 030T_S 120C_E 111U_S 030T_B 021D_S 210_S 111U_B 030T_E 021D_E 210_B 111U_E 021U_S 210_E 030C 021U_E 201_S 300 201_B Network Structure Regular Equivalence through triad distributions

  39. Block Model: School Network Structure Jefferson High School Sunshine High School School provides a good boundary for social relations School does not provide a good boundary for social relations

  40. Block Models Jefferson High School Sunshine High School 4% 34% 43% 32% 52% 33% Image networks. Width of tie is proportional to the ratio of cell density to mean cell density.

  41. Block Model Characteristics Jefferson High School Sunshine High School

  42. Block Model: Sunshine High School Jefferson High School Sunshine High School

  43. Correspondence of Field & Practice Jefferson High School • Being in the same block significantly increases the likelihood of being the same behavioral cluster • “Locally” defined: OR = 1.13 • “Globally” defined: OR = 1.12 • The effect is differential across blocks: • Being adjacent in the network has a consistent positive effect: • Local: OR = 1.21 • Global: OR = 1.35 • SES Similarity increases the odds of being in the same behavior profile Coefficients based on a dyad-level logistic regression model. Models control for grade and gender.

  44. Correspondence of Field & Practice Sunshine High School • Being in the same block barely increases the likelihood of being the same behavioral cluster • Locally defined: OR = 1.03 • Globally define” OR = 1.02 • The effect is differential across blocks: • Being adjacent in the network has a weaker, but still positive effect: • Local: 1.13 • Global: 1.08 • SES Similarity increases the odds of being in the same behavior profile Coefficients based on a dyad-level logistic regression model. Models control for grade, race and gender.

  45. Field, Practice & Adolescent Risk Behavior Delinquency Scale ranges from ‘never’ to “6 or more times” and is highly skewed. I dichotomize to identify the 25% who are most delinquent

  46. Field, Practice & Adolescent Risk Behavior Sexually Active Proportion who report having had sex Grade in school

  47. Field, Practice & Adolescent Risk Behavior School Attachment Mean of 3 items: - Happy to be at school - Feel a part of the school - Feel close to others at school

  48. Field, Practice & Adolescent Risk Behavior Jefferson High School: Delinquency • Core blocks in Jefferson are much more likely to be delinquent than either of the “insider” periphery blocks. • Periphery Insiders are 0.32 times as likely to be delinquent • Semi-Periphery Insiders are 0.53 times as likely to be delinquent Models control for SES, Sex, grade in school and family structure, values are odds rations for being delinquent.

  49. Field, Practice & Adolescent Risk Behavior Jefferson High School: Delinquency • Based on the Local activity profile, students in the “Non-active” working group are significantly less likely (OR = 0.309) to be delinquent. • Based on the Global activity profile, students in the “Non-School Active” group are significantly more likely to be delinquent. • Combining block membership and behavior profiles suggest that the three sources are largely independent, with each making significant contributions to the likelihood of delinquency. • The substantive effect of the network position variables seems highest • Followed by the effect of local behavior profile • The global behavior effects are the least powerful. Models control for SES, Sex, grade in school and family structure

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