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Record W3158518757 · doi:10.1080/09614524.2021.1911939

Why technocratic understandings of humanitarian accountability undermine local communities

2021· article· en· W3158518757 on OpenAlexfundno aff
Omer Aijazi

Bibliographic record

VenueDevelopment in Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAccountabilityTechnocracyCognitive reframingPoliticsPublic administrationPolitical scienceHumanitarian aidEquity (law)Public relationsSociologyLawPsychology

Abstract

fetched live from OpenAlex

Current trends in humanitarian accountability are unpacked through the examination of an accountability system put in place after the 2010 monsoon floods in Pakistan. Humanitarian accountability, when narrowly understood as a technical and procedural tool, can undermine local self-advocacy efforts, silence community dissent and supress broader equity claims. Reframing humanitarian accountability as a political and ethical project can inspire innovation, support frontline aid workers, and ignite the radical revisioning of the humanitarian contract itself.

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)0.015
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.043
Scholarly communication0.0120.011
Open science0.0010.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.051
GPT teacher head0.336
Teacher spread0.285 · 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 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

Citations8
Published2021
Admission routes1
Has abstractyes

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