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Record W2764788230 · doi:10.14452/mr-067-05-2015-09_5

Stripping Away Invisibility: Exploring the Architecture of Detention

2015· article· en· W2764788230 on OpenAlexaboutno aff
Victoria Law

Bibliographic record

VenueMonthly Review · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPrisonInvisibilitySociologyPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

tings chak, Undocumented: The Architecture of Migrant Detention (Montreal: Architecture Observer, 2014), 112 pages, 22 euros ($30.60 from Amazon), paperback. Over the past six years, more than 100,000 people, including children, have been jailed in Canada, many without charge, trial, or an end in sight, merely for being undocumented.… Locked away from the public eye, they become invisible.… Like the people within, immigrant detention centers are often invisible as well. Photos and drawings of these places are rarely public; access is even more limited. Canada has three designated immigrant prisons, and it also rents beds in government-run prisons to house over one-third of its detainees.… Undocumented: The Architecture of Migrant Detention begins to strip away at this invisibility. In graphic novel form, Toronto-based multidisciplinary artist tings chak draws the physical spaces of buildings in which immigrant detainees spend months, if not years. In crisp black and white lines, chak walks the reader through the journey of each of these 100,000+ people when they first enter an immigrant detention center. Click here to purchase a PDF version of this article at the Monthly Review website.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.367
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.029
Scholarly communication0.0140.005
Open science0.0020.009
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0300.002

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 head0.162
GPT teacher head0.352
Teacher spread0.190 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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