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Authordc.contributor.authorOrtega Ferrand, Lorena 
Authordc.contributor.authorBoda, Zsófia 
Authordc.contributor.authorThompson, Ian 
Authordc.contributor.authorDaniels, Harry 
Cita de ítemdc.identifier.citationInternational Journal of Educational Research 99 (2020) 101517es_ES
Abstractdc.description.abstractUnderstanding the structure of staff advice relationships and the factors that facilitate (and hinder) the flow of resources within schools is key to school improvement. Our study examines school staff advice networks for supporting vulnerable learners using Exponential Random Graph Models (ERGMs). We investigate the individual and structural mechanisms that shape these networks in six secondary schools and find evidence for the importance of mutuality, clustering and individual similarities. Educators tend to ask for advice from those in formal leadership or support positions, although informal hierarchies are also present. The study contributes with a novel application of an inferential social network approach to study patterns of advice relations among teachers, support staff and formal leaders in schools.es_ES
Patrocinadordc.description.sponsorshipOxford University John Fell Fund. PIA-CONICYT Basal Funds for Centers of Excellence Project: FB0003. College for Interdisciplinary Educational Research, a Joint Initiative of the BMBF. Jacobs Foundation. Leibniz Association.es_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile*
Link to Licensedc.rights.uri*
Sourcedc.sourceInternational Journal of Educational Researches_ES
Keywordsdc.subjectSocial network analysises_ES
Keywordsdc.subjectSchool staffes_ES
Keywordsdc.subjectAdvice networkses_ES
Títulodc.titleUnderstanding the structure of school staff advice relations: an inferential social network perspectivees_ES
Document typedc.typeArtículo de revistaes_ES
Indexationuchile.indexArtículo de publicación ISIes_ES

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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile