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Record W2751384874 · doi:10.1093/ia/iix150

Humanitarians at war: the Red Cross in the shadow of the Holocaust

2017· article· en· W2751384874 on OpenAlexaboutno aff
Bogdan C. Iacob

Bibliographic record

VenueInternational Affairs · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsThe HolocaustConsolidation (business)Shadow (psychology)LawPolitical scienceExistentialismEconomic historyHistoryEconomicsPsychology

Abstract

fetched live from OpenAlex

The International Red Cross conference was held in Toronto in 1952. The event signalled the postwar consolidation of the International Committee of the Red Cross' (ICRC) status as a high-profile independent humanitarian organization based in Geneva with an all-Swiss leadership. The situation was best described by ICRC president Paul Ruegger: ‘Today the position of the ICRC, after the Geneva diplomatic conference and since September 1948 in Stockholm, is quite strengthened in terms of its Swiss composition. Financially, we are not completely without funds; compared to the holdings of 200,000 francs in 1939, the deficit of 3 million francs in 1948, we now have 20 million francs at our disposal. Despite very tough fights on all sides, we move forward’ (p. 235). The statement points to two developments that defined the ICRC's history between 1939 and the early 1950s. On the one hand, by successfully reforming the Geneva Conventions (1949), the organization was instrumental in bringing about better protection of civilians in wartime. On the other hand, because of the decisions and actions of its leadership during the Second World War and in the years after, the ICRC experienced an existential crisis that put into question the validity of its brand of humanitarianism.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.036
Scholarly communication0.0140.007
Open science0.0010.006
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0070.001

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 head0.040
GPT teacher head0.263
Teacher spread0.223 · 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

Citations23
Published2017
Admission routes1
Has abstractyes

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