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Record W4405346936 · doi:10.24908/jcri.v11i2.18245

On the Poetics of Migration, Black Geographies, and Nervous Conditions

2024· article· en· W4405346936 on OpenAlexaffvenueabout
Paul Akpomuje, Adesoji Babalola, Milka Njoroge, Katherine McKittrick

Bibliographic record

VenueJournal of Critical Race Inquiry · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsQueen's University
Fundersnot available
KeywordsDiasporaPoeticsSociologyConversationQueen (butterfly)KinshipPoetryGender studiesCapitalismHappinessMedia studiesAnthropologyLiteratureArtPolitical scienceLaw

Abstract

fetched live from OpenAlex

This conversation began in Winter 2023, at Queen’s University in Kingston, Ontario, Canada. At the time we were collectively studying Black geographies. As faculty and students who are part of the Black diaspora yet have very different experiences of displacement, our discussions revolved around the uneasy connections between education, university life, migration, and Blackness. Inspired by the writings of Simone Browne, on January 25, 2024, the Revolutionary Demand for Happiness working group organized a conversation that revolved around the poetic possibilities of migration, mobility, immobility, borders, and boundaries. Paul Akpomuje and Aaliyah Strachan organized the event, and it was moderated by Katherine McKittrick. Akpomuje, a Nigerian poet and doctoral student in the Queen’s University Faculty of Education, read a set of his poems that discussed themes such as surveillance, visas, travel, and home. The poems were paired with community stories about displacement and belonging; we made connections between over-policing, governmentality and government papers, racial capitalism, family and kinship ties, and the difficult and onerous work of traveling as members of the Black diaspora. We also homed in on understanding the racialized underpinnings of the “international student” category at Queen’s University—a figure that is monetarily required-desired, yet is also rendered institutionally unrooted and out of place.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.044
GPT teacher head0.383
Teacher spread0.340 · 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 designTheoretical or conceptual
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
Published2024
Admission routes3
Has abstractyes

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