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International Accompaniment and Witnessing State Violence in the Philippines

2008· article· en· W2057955843 on OpenAlexaffabout
Geraldine Pratt

Bibliographic record

VenueAntipode · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSolidarityGrassrootsHuman rightsState (computer science)Power (physics)PoliticsInternational relationsPolitical scienceInternational communitySociologyLawPolitical economy

Abstract

fetched live from OpenAlex

Abstract: This paper is an examination of a fact‐finding mission by Canadian grassroots organizations to the Philippines in November 2006, focused on investigating the large number of extra‐judicial killings that have occurred since 2001. The mission accompanied KARAPATAN, a Philippines‐based human rights organization, with hopes that their international status would allow KARAPATAN access to militarized regions otherwise inaccessible to them, and that the international attention brought by Canadians would protect them from military violence. The paper tackles the ethics, politics and potentials of such international human rights solidarity, and both explores and unsettles conventional concerns about the power dynamics of international solidarity by considering the complexity of the positionings of the Canadian observers. These positionings both reproduce and disrupt static stable geographies of the global North/South. In Central Luzon, for instance, the politics and ethics of their status as outsiders was a persistent issue. In Southern Tagalog, however, the Canadian observers could not quite keep their distance, found that they were not as firmly located in their Canadian identities as they might have supposed, and not only observed but experienced the theatrics of state violence.

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)0.002
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.913

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0130.008
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.042
GPT teacher head0.332
Teacher spread0.290 · 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

Citations16
Published2008
Admission routes2
Has abstractyes

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