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Record W3192637765

Cross-platform Online Collaboration in Recognition of the Fifth Anniversary of the Attack on the MSF Trauma Center in Kunduz, Afghanistan

2020· article· en· W3192637765 on OpenAlexaff
Brian Cox

Bibliographic record

VenueSSRN Electronic Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsQueen's University
Fundersnot available
KeywordsHyperlinkLibrary sciencePublicationCenter (category theory)Political scienceWorld Wide WebWeb pageComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This cross-platform online collaboration was organized to publish a series of five essays on four separate online platforms in recognition of the fifth anniversary of the attack on the MSF trauma center in Kunduz Afghanistan. Each essay in the collaboration, which was published on October 3, 2020, precisely five years after the airstrke, examines a selected aspect of the attack and the discourse that followed. The essays were published by the Harvard International Law Journal online, Opinio Juris (in two parts), Just Security, and Lawfire. The manuscript posted here on SSRN presents each of the five essays in a single, consolidated file. Each file contains a hyperlink that navigates to the individual webpage where that particular essay can be found.

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)0.006
metaresearch head score (Gemma)0.019
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 score0.013
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.004
Scholarly communication0.0080.004
Open science0.0010.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.064
GPT teacher head0.342
Teacher spread0.279 · 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
Published2020
Admission routes1
Has abstractyes

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