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Record W7120752181

Ciganos, Roma e Gypsies: projeto identitário e codificação política no Brasil e Canáda

2013· dissertation· pt· W7120752181 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2013
Typedissertation
Languagept
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)NarrativeProcess (computing)Field (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Esta tese focaliza o processo de codificação política da identidade cigana no Brasil e Canadá, a partir de duas associações ciganas: a União Cigana do Brasil UCB, no Rio de Janeiro, e o Roma Community Center RCC, em Toronto. Neste estudo, examino o “projeto identitário” da UCB e do RCC, explorando as estratégias discursivas e representacionais acionadas por seus agentes políticos para a construção de uma identidade cigana ou roma na esfera pública. Analisando como símbolos, discursos, narrativas e estereótipos são apropriados e imaginados por agentes políticos, que representam essas associações, apresento narrativas nacionais sobre os ciganos. A pesquisa foi baseada em trabalho de campo “multi local”, compreendendo o período de 2008 a 2012, e teve como foco agentes políticos (nacionalistas ciganos) e atores (ciganos) que não estão engajados na construção de uma identidade cigana pública. Esses atores resistem ao processo de codificação política da identidade cigana, afirmando particularismos étnicos. Além disso, eles resistem à exposição de sua etnicidade na esfera pública, assim como ao conteúdo dos projetos identitários apresentados pelas associações. Esta tese mostra que na “intimidade cultural”, a identidade cigana é construída em confronto com a identidade “harmoniosa” e “unificada” do discurso nacionalista.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.722

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0210.009
Scholarly communication0.0090.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.318
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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