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Record W1588965515

Displacement and Identity: Igbo Diaspora of Canada, 1965-1985

2015· article· en· W1588965515 on OpenAlexaboutno aff
Obinna U. Muoh

Bibliographic record

VenueJournals & Books Hosting (International Knowledge Sharing Platform) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsIgboDiasporaGender studiesPoliticsIdentity (music)ImmigrationSociologySecessionSpanish Civil WarContext (archaeology)Political scienceEthnologyGeographyLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Between 1965 and 1985, a significant number of Igbo, one of the three major cultural groups in Nigeria, migrated to Canada. This group of immigrants consists of victims of socio-political displacements that arose from the Nigerian civil war, which was fought when this cultural group attempted secession from Nigeria under the auspices of the Republic of Biafra, between July 6, 1967-January 15, 1970. As many Igbo began to leave Nigeria in search of a safe haven, Canada became one of the destinations for a significant proportion of the privileged class. It was certainly the knowledge of their previous encounters that propelled their choice of Canada. On arrival, they established socio-political organizations that created a sense of separate identity from the wider Nigerian community in Canada. This study focuses on the migration and identity formation of the second stream of Igbo immigrants in Canada, It highlights how displacement and victimization during the Nigerian civil war has propelled Igbo migration to Canada, and how their memories shaped their identity and activities in Canada. By examining the Igbo experiences during this period, the study situateS the Igbo Diaspora in Canada within a wider context, and in so doing, bring academic attention to the socio-political dimension of Igbo Diaspora. Keywords : Displacement, Identity, Diaspora, Migration

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.083
GPT teacher head0.364
Teacher spread0.281 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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