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Record W2947051283 · doi:10.4103/intv.intv_16_18

Thoughts from Afghanistan: Rebuilding community in complexity

2018· article· en· W2947051283 on OpenAlexaff
Athena Madan

Bibliographic record

VenueIntervention · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsRoyal Roads UniversityUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAfghanReflection (computer programming)PoliticsIntervention (counseling)Field (mathematics)PermissionPolitical scienceWork (physics)Public relationsSociologyPsychologyLawComputer scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

This personal reflection shares four vignettes from the author’s field journal while on assignment in Afghanistan. Note 1 shares the thoughts (with permission) of a few of her female Afghan colleagues; Notes 2 and 3 share experiences from field work day-to-day; and Note 4 closes with a reflection about some of the larger socio-political complexities that may tacitly underpin humanitarian intervention in Afghanistan. This reflection piece offers no answers, only musings.

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)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0490.043
Scholarly communication0.0120.011
Open science0.0020.016
Research integrity0.0060.016
Insufficient payload (model declined to judge)0.0060.001

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 head0.106
GPT teacher head0.392
Teacher spread0.286 · 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 designNot applicable
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

Citations2
Published2018
Admission routes1
Has abstractyes

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