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Record W4200060524 · doi:10.51442/ijags.0018

“On the High Seas with no Place to Land”: The Smyrnaean Inferno and Humanitarian Aid to Armenian and Greek Refugees from Turkey (1922-1923)

2021· article· en· W4200060524 on OpenAlexaff
Joceline Chabot, Sylvia Kasparian

Bibliographic record

VenueInternational Journal of Armenian Genocide Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsArmenianRefugeeHumanitarian aidNationalismContext (archaeology)Political sciencePopulationGratitudeGovernment (linguistics)Ancient historyRelief WorkSpanish Civil WarTurkishEconomic growthHistoryLawSociologyMedicineArchaeologyPoliticsDemography

Abstract

fetched live from OpenAlex

In September 1922, the great fire of Smyrna drove more than 200,000 Armenian and Greek refugees to the wharves of that port city. They had fled to Smyrna to escape the massacres perpetrated by Turkish nationalist troops and now urgently needed humanitarian aid to relocate them to safety in Greece. In this article we examine the actions and the roles of humanitarian workers of the Near East Relief (NER) and the American Women’s Hospitals (AMH) working in Greece among these refugees deported from Smyrna. We highlight the central role of women doctors and nurses in their humanitarian efforts to save this population. Their actions, and the gratitude of their peers and government authorities, solidified their professional status in the context of profound changes to transnational humanitarianism after 1919.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.245
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

Citations1
Published2021
Admission routes1
Has abstractyes

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