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Record W7096073114

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2006· article· en· W7096073114 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsSecuritizationConceptualizationArgument (complex analysis)Nexus (standard)Circumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

Nation-states around the globe, especially Western ones, are cracking down on migration for security reasons. Notwithstanding this rapid securitization of the movement of people, the migration-security nexus remains under analyzed and unelaborated in security studies. Among the limited number of security theories that provide a satisfactory, albeit partial, framework for tackling the issue of migration, securitization theory stands out clearly. Indeed, securitization theory proves to be useful in examining the migration-security linkage. Yet serious problems arise when securitization theory is analyzed in greater depth. I argue that securitization theory displays internal inconsistency in its treatment of the interaction between actors and audience and presents an inadequate conceptualization of structures. Ultimately, securitization theory needs to be amended. The argument is supported by an analysis of Canada’s experience with migration from 1989 to 2005.

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)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.459
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0090.005
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.5410.346

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 head0.015
GPT teacher head0.319
Teacher spread0.304 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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