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Record W2312681977 · doi:10.5539/jsd.v9n2p137

Migration and Cultural Identity Retention of Igbo Migrants in Ibadan, Nigeria

2016· article· en· W2312681977 on OpenAlexvenueno aff
Ajani Oludele Albert, Onah Onodje

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobalization and Cultural Identity
Canadian institutionsnot available
Fundersnot available
KeywordsIgboEthnic groupFocus groupAgency (philosophy)Cultural identityPromotion (chess)Identity (music)Thematic analysisExploratory researchGender studiesIndigenousGeographySociologySocioeconomicsEthnologyPolitical scienceAnthropologySocial scienceQualitative researchEcologyBiology

Abstract

fetched live from OpenAlex

Nigeria, a country of 170 million people and 250 ethnic nationalities presents a complex picture of internal migration within its geographical entity. This study investigated the issues relating to cultural identity retention among a highly migratory ethnic group, the Igbo, whose origin is in the Eastern part of Nigeria. The study employed exploratory research design. Twenty-five in-depth interviews were conducted and two focus group discussion sessions were held with members of Eha Alumona home town association in Ibadan, a city in the south western Nigeria. Data were collected during the association’s meetings and other cultural activities involving the members of the group. The study adopted thematic content analysis of its data. The findings indicate that the Igbo migrant association was a very active agency in the promotion of Igbo cultural identity among its members. Both material and non-material cultural elements were equally affected in the process of adaptation by the migrants. The study concludes that though the migrants indicated a high level of integration into their host culture, they continued to retain certain cultural elements of their community of origin.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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