MétaCan
Menu
Back to cohort
Record W2569500079 · doi:10.7202/1037516ar

Sur la frontière

2016· article· fr· W2569500079 on OpenAlexaffvenueabout
Bruce G. Miller, Anne-Hélène Kerbiriou

Bibliographic record

VenueAnthropologie et Sociétés · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

En cette ère de déclin de la capacité de l’État à contrôler ses frontières, l’une des solutions a consisté à créer des « spectacles de pouvoir », à savoir des murs et barrières fortifiés. Sur le territoire des Salish du littoral en Colombie-Britannique et dans l’État de Washington, ces barrières ont entravé les déplacements légaux des peuples autochtones. En me basant sur un travail de terrain et sur ma participation en tant qu’expert et témoin, je me concentre sur deux cas d’impacts négatifs sur les Premières Nations. Le premier concerne un homme des Premières Nations arrêté par la Sécurité intérieure américaine et des agents fédéraux pour avoir pêché dans des eaux américaines qui se trouvaient faire partie des lieux de pêche historiques de sa nation. Le second concerne une communauté frontalière dont le Conseil utilise la frontière comme un moyen d’enlever toute reconnaissance légale à 306 de ses propres membres. Ces histoires traduisent une contestation désorganisée de l’État et des autorités tribales légitimes, qui tous affirment leur primauté sur un autre tenu pour quantité négligeable. Cela a eu pour conséquence de rendre plus répressives les régions frontalières des Salish du littoral.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0060.008
Scholarly communication0.0070.005
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0630.010

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 head0.121
GPT teacher head0.519
Teacher spread0.398 · 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 designQualitative
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
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueAnthropologie et SociétésSame topicMigration, Health, Geopolitics, Historical GeographyFrench-language works237,207