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'It still matters': The role of skin colour in the everyday life and realities of black African migrants and refugees in Australia

2018· paratext· en· W4247959908 on OpenAlexaff

Bibliographic record

VenueAustralasian Review of African Studies · 2018
Typeparatext
Languageen
FieldSocial Sciences
TopicInterdisciplinary Cultural and Social Studies
Canadian institutionsUniversity of TorontoInstitute on Governance
FundersUniversity of CambridgeUniversity of MichiganPrinceton UniversityUniversity of MelbourneWorld Bank Group
KeywordsPolitical science

Abstract

fetched live from OpenAlex

This article looks at the everyday life and realities of some of Australia’s most recent immigrant communities, by shedding light on the experiences of black Africans in Queensland. Particularly, this article examines the experiences of black African migrants and refugees living in South East Queensland, to better understand how race, skin colour and immigration status interact to shape their everyday lives and social location in Australia. Data were collected from 30 participants using qualitative research methods. The theoretical approach employed synthesises concepts from identity, blackness, race and racism, whiteness and critical race theory. The subjective experiences of the participants interviewed indicate that skin colour still matters in determining life chances for black Africans in Australia. While the empirical focus is specific to Australia, this article contributes to the research literature in valuable ways, both from a theoretical perspective and in terms of a comparative contextualisation of racism.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.371
Teacher spread0.329 · 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
Published2018
Admission routes1
Has abstractyes

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