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Record W2529795334 · doi:10.15173/glj.v7i3.3022

Review of: Moritz Ege (2013), »Ein Proll mit Klasse«: Mode, Popkultur und soziale Ungleichheiten unter jungen Männern in Berlin, and Roberto Camargos (2015), Rap e Rap e Política: Percepções da vida social brasileira

2016· article· de· W2529795334 on OpenAlexvenueno aff
Bernhard Leubolt

Bibliographic record

VenueGlobal Labour Journal · 2016
Typearticle
Languagede
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

This review covers two books on a similar subject, but in different socio-economic contexts. Both deal with the subculture of rap and hip hop, albeit from different theoretical and methodological backgrounds. Moritz Ege's work Ein Proll mit Klasse: Mode, Popkultur und soziale Ungleichheiten unter jungen Mnnern in Berlin (A Prole with Class: Fashion, Pop Culture and Social Inequalities among Young Men in Berlin) is an ethnographic cultural analysis of Berlin's male sub-proletariat of the early 2000s. It is thereby situated in one of the centres of the Global North, where deindustrialisation and the precarisation of the workforce led to a dramatic increase of social exclusion (Bude and Willisch, 2008; Castel and Drre, 2009). Roberto Camargos' Rap e Poltica: Percepes da vida social brasileira (Rap and Politics: Perceptions of Brazilian Social Life) is methodologically based on conceptions of "history from below" (Camargos, p. 28) and deals with the emergence and development of politically engaged rap from the Brazilian peripheries from the 1980s to the mid-2000s. Thus Camargos writes about cultural politics (Alvarez, Dagnino and Escobar, 1998) of the marginalised in one of the most unequal countries in the Global South. Differing from Germany, Brazilian exclusion has its roots in slavery and has affected a majority of the population throughout history.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.274
Teacher spread0.254 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations5
Published2016
Admission routes1
Has abstractyes

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