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Record W2099939260 · doi:10.1177/1368431011423594

Psychoanalytic theory and border security

2012· article· en· W2099939260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEuropean Journal of Social Theory · 2012
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsUniversity of Ottawa
FundersCentre for Research in the Arts, Social Sciences and Humanities, University of CambridgeSocial Sciences and Humanities Research Council of Canada
KeywordsClearancePsychoanalytic theoryNational securitySign (mathematics)Political economySociologyBorder SecurityIdentification (biology)Law and economicsEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Freezing is a common sign of panic, a response to accidents or events that overflow our capacity to react. Just as all civil airspace was cleared after the 9/11 attacks, the US-Canada border was also frozen, causing economic slowdowns. Border policies are caught between these two panics: security failures and economic crisis. To escape this paradox, American and Canadian authorities have implemented a series of security measures to make the border ‘smarter’, notably the implementation of biometric identity documents and surveillance by UAV Predator drones. Psychoanalytic theory can help us explain why the Canadian and American governments have invested so much money for so little evident or measurable increase in either security or economic flows. The article uses the notion of phantastic objects to explain these (over-)reactions to risk management at the US-Canada border.

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.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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