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Record W4417170962 · doi:10.51137/wrp.ijarbm.326

A Qualitative Case Study of Experience of Xenophobia Among Francophone African Informal Immigrant Entrepreneurs in Pretoria

2025· article· W4417170962 on OpenAlexaff
Gallous Atabongwoung, Mosa Nkoko

Bibliographic record

VenueInternational Journal of Applied Research in Business and Management · 2025
Typearticle
Language
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsXenophobiaFrenchImmigrationInformal sectorQualitative researchFace (sociological concept)Participant observationQualitative property

Abstract

fetched live from OpenAlex

Francophone African immigrants in South Africa find it difficult to find formal employment because of exclusive laws and the challenge of language barriers. Accordingly, they frequently resort to informal businesses which expose them to acts of xenophobia. Xenophobia and Francophone African informal immigrant entrepreneurs have negative and positive consequences in South Africa. This article presents a descriptive account of individual experiences of xenophobia among thirty (30) Francophone African informal immigrant entrepreneurs in Pretoria during the conduct of their business. It therefore, seek to answer the following questions; (a) How are Francophone African informal immigrant entrepreneurs discriminated against while conducting their business in Pretoria? (b) What type of harassment do they face while conducting their business in Pretoria? (c) Why are they attacked while conducting their business in Pretoria? This descriptive qualitative case study adopts content analysis to describe the experience of xenophobia among Francophone African informal immigrant entrepreneurs in Pretoria. The findings reveal “skipping” Francophone African informal immigrant entrepreneurs to buy from South African informal traders is an experience of discrimination. It establishes virtual, verbal, and physical harassments Francophone African informal immigrant entrepreneurs experience while conducting their business in Pretoria. It demonstrates that the failure to lend money to South Africans or calling police on locals attract violent attacks against Francophone African informal immigrant entrepreneurs while conducting their business in Pretoria.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.112
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.410
Teacher spread0.362 · 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.

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
Published2025
Admission routes1
Has abstractyes

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