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Record W3214990526 · doi:10.25071/1920-7336.40958

Introduction: Humanizing Studies of Refuge and Displacement?

2021· article· en· W3214990526 on OpenAlexaffvenue
Hanno Brankamp, Yolanda Weima

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsYork University
FundersUniversity of Oxford
KeywordsDisplacement (psychology)Environmental sciencePsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

This forum of Refuge offers interventions around the theme Humanizing Studies of Refuge and Displacement? as a theoretical and methodological debate for critical refugee and forced migration scholarship. However, rather than proposing a conclusive path towards humanization—which encompasses complex processes of (re)building, (re)constructing, and (re)thinking “the human,” humanity, and social relations—our aim is more modest, tentative, and reflexive. Our starting point was a workshop co-organized by the authors and Patricia Daley at the University of Oxford in November 2018. The workshop brought together an interdisciplinary set of scholars to reflect collectively on dehumanizing tendencies in the ontologies, epistemologies, and methodologies underpinning scholarship on refugees today, and to think through, beyond, and against them.
\nTaking this event as an entry, we use humanization as a heuristic to accommodate multiple contradictory versions of what more emancipatory scholarship might entail. We are not only concerned with tracing, traversing, and pondering over our positionalities and epistemic complicities, or charting “the border between theory and activism” (Lafazani, 2012; Torres, 2018). Instead, we actively seek to practise and advance a radical scholarship that is grounded in political solidarity for social and racial justice. To do so means grappling with, and situating ourselves and our scholarly institutions within, abiding structures of violence and erasure that are—sometimes slowly, sometimes more spectacularly—perpetrating the very ontological destruction of people on the move that we are desperately trying to combat.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.325
Teacher spread0.298 · 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 designNot applicable
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

Citations7
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueRefuge Canada s Journal on RefugeSame topicMigration, Refugees, and IntegrationFrench-language works237,207