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Schools in Jicamarca and Villa El Salvador

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Community role of schools in Jicamarca and Villa El Salvador (Lima).

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Schools in Jicamarca and Villa El Salvador

  1. 1. Behavior settings and personal networks in Jicamarca and Villa el Salvador (Peru): The community role of schools Isidro Maya-Jariego, Irene Cano, Daniel Holgado, Esperanza Márquez, Natalia Rodríguez & Fran Santolaya Mixed methods, social networks and community interventions: international workshop Sevilla, May 17 2016
  2. 2. Personal networks and settings in the community Background • In Ecological Psychology a behaviour setting is defined by having a place, time and a standing pattern of behaviour (Barker, 1968). • Settings typically create predictable relationships among their members, and those qualities persist over time regardless of the individuals involved (Seidman, 1988, 1990). They are social regularities. • Settings may differ in the relevance they have for community building: previous research has shown that schools are community hubs (Clandfield & Martell, 2010; Neal & Watling Neal, 2012).
  3. 3. Personal networks and settings in the community Aim • Our proposal is to describe neighbourhoods through a collection of relevant behaviour settings and their relationships among them. • Through samples of personal networks in specific communities we depict the patterns of relationships in a set of very frequented places in the neighbourhood. • We pay particular attention to the role of schools and the potential impact in terms of bonding and bridging social capital.
  4. 4. • Three schools in Lima: Nassae (Jicamarca), Max Uhle and Peruano Suizo (Villa El Salvador). • Jicamarca is a very recent settlement, not urbanized, while the other two schools are at different stages of Villa El Salvador. • Villa El Salvador is also on the outskirts of the city, but has a history of community self-organization, especially in the older areas, where the school Peruano Suizo is located. • ”Edúcame Primero, Peru” (EPP) is a psycho-educational program to prevent child labor and to improve educational experience of children at risk. Study context: preventing child labour in Lima (Peru)
  5. 5. Jicamarca and Villa El Salvador (Peru)
  6. 6. Jicamarca and Villa El Salvador (Peru)
  7. 7. Methods Participants • The fieldwork focused in 3 neighbourhoods in the outskirt of Lima where the program EPP was implemented: • 2 in Villa el Salvador and 1 in Jicamarca • The criterion to be included was to be parents or tutor of children that study in one of the three schools participating in the program: Nassae, Max Uhle and Peruano Suizo. • In total 138 parents were interviewed, obtaining information on their personal networks, family involvement in school, social support and sense of community, household characteristics, as well as child labour conditions of their children (if any).
  8. 8. Methods Name generator • “Please give me a list of 45 people with whom you have regular relationship throughout the week. Please mention those with whom you have a more frequent and regular contact. [They may be co-workers, neighbours, family, friends, people with whom you share hobbies, and so on. They may be in your neighbourhood, nearby neighbourhoods or even other districts. It is important that they are the 45 people with whom you have a more frequent relationship]”. • Valued relationships: • 0. “They do not know each other, they have no relationship or no contact” • 1. “They know each other”. • 2. “They have some relationship”. • 3. “They have a strong relationship or are friends”
  9. 9. Methods Personal network data • Fixed number of alteri (McCarty, 2002), both to capture the diversity of structures of personal networks and to facilitate comparisons and data processing. • Valued and symmetric matrices (45x45 alteri) were processed, analysed and visualised with Ucinet 6 (Borgatti, Everett & Freeman, 2002) and Visone (Brandes y Wagner, 2004). • 138 personal networks of 45 alteri (990 edges). • 6.210 alteri and 136.620 relationships were analysed in total.
  10. 10. Methods Two strategies • Centrality and cohesion measures to compare the structure and composition of personal networks (McCarty, 2002): • Centrality Measures: Degree, Betweenness, Eigenvector, Closeness, Degre Centralization, Betweenness Centralization. • Cohesion Measures: Cliques, Components, Density, E-I Index, IQV Index. • Clustered graphs for summarising and comparing personal networks (either at the individual or aggregate levels) (Brandes, Lerner, Lubbers, McCarty & Molina, 2008, Lerner et al. 2007, 2008, Molina, Lerner & Gómez, 2008; García Macías, 2013; Maya Jariego, Holgado & Florido, in press).
  11. 11. Methods Clustered graphs • Respondents provided information on the neighbourhood, as well as the specific place where interaction more frequently take place which each alter: • A list of different specific places were summarised in 7 main places of interaction: ego house, other houses in the neighbourhood, school, workplace, market, church and telephone contact. • More generally we also distinguish whether the contacts were taking place preferably in the neighbourhood, outside the neighbourhood or via phone. • Three procedures to reduce networks complexity through grouping and clustering nodes in the same category or cluster, comparing intra- class and interclass ties: • Number of links: e (A, B) • Density of ties: e (A, B)/ (A*B) • Edge Weights: e (A, B)/√(A*B)
  12. 12. Frequency of relationships in each place
  13. 13. From personal networks to clustered graphs Relationships within and between spaces of the neighbourhood Relationships inside and outside the neighbourhood
  14. 14. From personal networks to clustered graphs Local networks and role of schools • The place with the greater centrality is the home of the respondent, around which the personal network articulates. • School is (a) the second best connected, (b) with the highest intra-group density, and (c) it is especially well connected with ego house, and workplace. • There seems to be a core-periphery distribution from neighborhood of the respondent to other neighborhoods to phone contacts.
  15. 15. Relationships and places in three neighbourhoods
  16. 16. Relationships and places in three neighbourhoods Recent settlement versus established communities • Peruano Suizo school has the most articulated network of places, while Max Uhle's and Nassae's networks have less density. • Peruano Suizo school seems to be essential for relationships both within and outside the neighborhood: it is a densely connected space, well connected with the house of respondents, as well as outside the neighborhood (workplace). • In Max Uhle environment there are other relevant places such as the market and other homes. • In Nassae the neighborhood seems to be scarcely articulated. The school is salient in a poorly structured environment.
  17. 17. Networks, communities and child labor
  18. 18. Networks, communities and child labor Prevalence and intensity • Child labor rate: 21 children out of a total of 138 performed "last week some kind of work on payment for an hour or more" (15.21%). • 6 children work permanently and outside of the family (4.35%). • The prevalence and intensity of child labor time is greater in Nassae (Jicamarca). Max Uhle stands for the contribution child labor represent for the family.
  19. 19. From structure of relationships to community integration
  20. 20. From structure of relationships to community integration Structure, community and child labor • The scale of community integration correlated significantly with intra- class weight of contacts in another home in the neighborhood (r = .469, p <.05), the intra-class weight of telephone contacts (r = .386, weight p <.01) and weight of relations between home of ego and another home in the neighborhood (r = .558, p <.01). • Both the density of relations between households in the neighborhood (B = .210, p <.01), as connectivity between the interviewee's home and other homes in the neighborhood (B = .133, p <.01) are associated with higher levels of community integration. • Relevance of child labor correlates significantly with the number of components of the personal network (r = .216, p <.05), with intra-rol weight of market contacts (r = .303, p < .05), with intra-role weight of telephone contacts (r = 292, p <.05), and the weight of relationships between the market and home of ego (r = .458, p <.01).
  21. 21. Conclusions Child labor in Jicamarca and Villa El Salvador • The school is the second most significant context of interaction in the neighborhood. It is a space where relationships with other families in the neighborhood are initiated, with opportunities for interaction reflected in comparatively high indicators of density and transitivity. • The density between the different spaces of sociability is lower in the most recent settlement, or where the geographical mobility of residents to other parts of Lima is more common.
  22. 22. Conclusions Child labor in Jicamarca and Villa El Salvador • In Jicamarca and Villa El Salvador we found a rate below the national average, but doubling (and in some cases tripling) the regional average. The highest rate occurs in the most recent settlement, coinciding with the less structured community environment. • Child labor is associated with a more fragmented network of places (with more components and more cliques); and personal networks where there are emerging spaces, alternative to households, among the most relevant contexts for interaction in the neighborhood.
  23. 23. Networks and communities in Jicamarca and Villa El Salvador Gracias Laboratorio de Redes Personales y Comunidades http://personal.us.es/isidromj Proyecto: Comunidades preparadas para la prevención del trabajo infantil. Educación, desarrollo psicológico y dinamización comunitaria de niños y niñas trabajadores en Lima (Perú) (2013-2016). Proyectos de Cooperación Internacional al Desarrollo de las Universidades Públicas Andaluzas. Agencia Andaluza de Cooperación Internacional al Desarrollo.

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