{"id":"https://openalex.org/W4391664703","doi":"https://doi.org/10.1109/siie59826.2023.10423698","title":"School dropout in the Federal Network Education of Brazil: is it an inherent individual attribute or it lies on setting conditions?","display_name":"School dropout in the Federal Network Education of Brazil: is it an inherent individual attribute or it lies on setting conditions?","publication_year":2023,"publication_date":"2023-11-16","ids":{"openalex":"https://openalex.org/W4391664703","doi":"https://doi.org/10.1109/siie59826.2023.10423698"},"language":"en","primary_location":{"id":"doi:10.1109/siie59826.2023.10423698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siie59826.2023.10423698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Symposium on Computers in Education (SIIE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082140349","display_name":"Jabson Cavalcante Dias","orcid":"https://orcid.org/0000-0003-4723-5432"},"institutions":[{"id":"https://openalex.org/I41458283","display_name":"Universidade Federal do Tocantins","ror":"https://ror.org/053xy8k29","country_code":"BR","type":"education","lineage":["https://openalex.org/I41458283"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Jabson Cavalcante Dias","raw_affiliation_strings":["Federal University of Tocantins,Palmas, TO,Brazil,77001-090"],"affiliations":[{"raw_affiliation_string":"Federal University of Tocantins,Palmas, TO,Brazil,77001-090","institution_ids":["https://openalex.org/I41458283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093894134","display_name":"Tadeu Lucena Da Silva","orcid":null},"institutions":[{"id":"https://openalex.org/I41458283","display_name":"Universidade Federal do Tocantins","ror":"https://ror.org/053xy8k29","country_code":"BR","type":"education","lineage":["https://openalex.org/I41458283"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Tadeu Lucena Da Silva","raw_affiliation_strings":["Federal University of Tocantins,Palmas, TO,Brazil,77001-090"],"affiliations":[{"raw_affiliation_string":"Federal University of Tocantins,Palmas, TO,Brazil,77001-090","institution_ids":["https://openalex.org/I41458283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093894135","display_name":"Marco Ant\u00f4nio Juliatto","orcid":null},"institutions":[{"id":"https://openalex.org/I41458283","display_name":"Universidade Federal do Tocantins","ror":"https://ror.org/053xy8k29","country_code":"BR","type":"education","lineage":["https://openalex.org/I41458283"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marco Ant\u00f4nio Juliatto","raw_affiliation_strings":["Federal University of Tocantins,Palmas, TO,Brazil,77001-090"],"affiliations":[{"raw_affiliation_string":"Federal University of Tocantins,Palmas, TO,Brazil,77001-090","institution_ids":["https://openalex.org/I41458283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009521006","display_name":"Adriano Nascimento da Paix\u00e3o","orcid":"https://orcid.org/0000-0002-2717-3716"},"institutions":[{"id":"https://openalex.org/I59606676","display_name":"Universidade Federal do Par\u00e1","ror":"https://ror.org/03q9sr818","country_code":"BR","type":"education","lineage":["https://openalex.org/I59606676"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Adriano Nascimento Da Paix\u00e3o","raw_affiliation_strings":["Federal University of Para&#x00ED;ba,Statistic Department,Para&#x00ED;ba, PB,Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Para&#x00ED;ba,Statistic Department,Para&#x00ED;ba, PB,Brazil","institution_ids":["https://openalex.org/I59606676"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068784622","display_name":"David Nadler Prata","orcid":"https://orcid.org/0000-0002-1414-4000"},"institutions":[{"id":"https://openalex.org/I41458283","display_name":"Universidade Federal do Tocantins","ror":"https://ror.org/053xy8k29","country_code":"BR","type":"education","lineage":["https://openalex.org/I41458283"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"David Nadler Prata","raw_affiliation_strings":["Federal University of Tocantins,Institute of Regional Development, Graduate Program of Computational Modeling,Palmas, TO,Brazil,77001-090"],"affiliations":[{"raw_affiliation_string":"Federal University of Tocantins,Institute of Regional Development, Graduate Program of Computational Modeling,Palmas, TO,Brazil,77001-090","institution_ids":["https://openalex.org/I41458283"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082140349"],"corresponding_institution_ids":["https://openalex.org/I41458283"],"apc_list":null,"apc_paid":null,"fwci":0.9591,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82533075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10457","display_name":"Education Pedagogy and Practices","score":0.8848999738693237,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10457","display_name":"Education Pedagogy and Practices","score":0.8848999738693237,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14241","display_name":"Evasion and Academic Success Factors","score":0.8331999778747559,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14274","display_name":"Education and Vocational Training","score":0.7817999720573425,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.9359447360038757},{"id":"https://openalex.org/keywords/school-dropout","display_name":"School dropout","score":0.6111700534820557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5068593621253967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14130860567092896},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.13591301441192627},{"id":"https://openalex.org/keywords/socioeconomics","display_name":"Socioeconomics","score":0.08853092789649963}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.9359447360038757},{"id":"https://openalex.org/C3017496549","wikidata":"https://www.wikidata.org/wiki/Q780562","display_name":"School dropout","level":2,"score":0.6111700534820557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5068593621253967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14130860567092896},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.13591301441192627},{"id":"https://openalex.org/C45355965","wikidata":"https://www.wikidata.org/wiki/Q1643441","display_name":"Socioeconomics","level":1,"score":0.08853092789649963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siie59826.2023.10423698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siie59826.2023.10423698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Symposium on Computers in Education (SIIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1755925439","https://openalex.org/W1909216329","https://openalex.org/W1967432541","https://openalex.org/W1983288443","https://openalex.org/W2004147962","https://openalex.org/W2030318182","https://openalex.org/W2031445243","https://openalex.org/W2063258553","https://openalex.org/W2084005400","https://openalex.org/W2123115557","https://openalex.org/W2146286549","https://openalex.org/W2156484891","https://openalex.org/W2162897826","https://openalex.org/W2229706076","https://openalex.org/W2285054073","https://openalex.org/W2479921892","https://openalex.org/W2752120314","https://openalex.org/W2767942197","https://openalex.org/W2789447613","https://openalex.org/W2797302139","https://openalex.org/W2810022699","https://openalex.org/W2889988224","https://openalex.org/W2910995661","https://openalex.org/W3021933707","https://openalex.org/W3035707715","https://openalex.org/W3103966268","https://openalex.org/W3165610528","https://openalex.org/W3201153983","https://openalex.org/W3207947368","https://openalex.org/W3210415906","https://openalex.org/W4200397450","https://openalex.org/W4214595106","https://openalex.org/W4226232432","https://openalex.org/W6609445178","https://openalex.org/W6610040026","https://openalex.org/W6629711222","https://openalex.org/W6632833553","https://openalex.org/W6634508654","https://openalex.org/W6686484161"],"related_works":["https://openalex.org/W2903194986","https://openalex.org/W3209595268","https://openalex.org/W1939009833","https://openalex.org/W52471014","https://openalex.org/W3199990854","https://openalex.org/W2909277982","https://openalex.org/W2336889554","https://openalex.org/W2608496095","https://openalex.org/W4243728289","https://openalex.org/W2953515775"],"abstract_inverted_index":{"Studies":[0],"shown":[1,122],"that":[2,64,90,123],"school":[3,49,59,70,128],"dropout":[4],"among":[5],"young":[6,42],"people":[7,43],"in":[8,96,138,153],"Brazil":[9],"corresponds":[10],"to":[11,20,48,55,67,73,79,86,110,134],"3%":[12],"of":[13,98,148],"the":[14,37,80,87,111,143],"annual":[15],"GDP":[16],"and":[17,23,82,127,145,150],"is":[18,33,72],"equivalent":[19],"all":[21],"state":[22],"municipal":[24],"spending":[25],"on":[26],"basic":[27,45],"education":[28,46],"per":[29],"year.":[30],"The":[31],"expectation":[32],"that,":[34],"each":[35],"year,":[36],"country":[38],"has":[39],"approximately":[40],"575,000":[41],"without":[44],"due":[47],"dropout.":[50],"Many":[51],"aspects":[52],"can":[53,65,131],"lead":[54],"greater":[56],"or":[57],"lesser":[58],"dropouts.":[60,101],"An":[61],"important":[62],"issue":[63],"help":[66],"understand":[68,135],"this":[69,103],"phenomenon":[71],"disentangle":[74],"which":[75,83],"attributes":[76],"are":[77,84],"inherent":[78],"individual":[81],"attributed":[85],"setting,":[88],"so":[89],"public":[91],"policies":[92],"could":[93],"be":[94,132],"developed":[95],"favor":[97],"reducing":[99],"schools\u2019":[100,140],"In":[102],"work,":[104],"logistic":[105],"regression":[106],"methods":[107],"were":[108],"applied":[109],"2019":[112],"Nilo":[113],"Pe\u00e7anha":[114],"Platform":[115],"databases":[116],"(approximately":[117],"250":[118],"thousand":[119],"records).":[120],"Results":[121],"demographic,":[124],"geographic,":[125],"economic,":[126],"setting":[129],"variables":[130],"measured":[133],"their":[136],"impacts":[137],"projecting":[139],"dropouts,":[141],"enabling":[142],"elaboration":[144],"carrying":[146],"out":[147],"preventive":[149],"corrective":[151],"actions":[152],"schools.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
