MétaCan
Menu
Back to cohort
Record W2805809757 · doi:10.1177/2153368718780219

I Am Nobody Here: Institutional Humanism and the Discourse of Disposability in the Lives of Criminalized Refugee Youth in Canada

2018· article· en· W2805809757 on OpenAlexaffabout
Jenny Francis

Bibliographic record

VenueRace and Justice · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRefugeeSociologyHumanismDehumanizationGender studiesCriminologyBiopowerIdeologyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

This article uses the concept of “institutional humanism” to explicate how the ideology of humanism is deployed through a biopolitical “discourse of disposability” to dehumanize, objectify, and animalize racialized and criminalized refugee youth in Canada, setting them in opposition to mainstream Whites who are deemed normal, rational, and autonomous—in essence, human. This article identifies four mechanisms of disposability: the expulsion of criminalized refugee youth from school and the labor market, the “revolving door” of the criminal justice system, the creation of deportability, and disinvestment in programs for youth. The treatment of criminalized refugee youth as disposable is part of an epistemological and ontological exercise that creates and enforces a boundary between those defined as human and those who are excluded from the set of “bodies that matter.” The study was conducted through qualitative interviews with criminalized refugee youth and professional adults who work with them. The interview data are set within the web of theoretical relationships among humanism, posthumanism, animalization, institutional policy, and categorizations based on race, gender, class, ability, age, and immigration status, demonstrating how these theoretical nodes attain bolder relief when operationalized under performativity.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.338
Teacher spread0.310 · 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

Citations13
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueRace and JusticeSame topicMigration, Health and TraumaFrench-language works237,207