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Record W6988462373

�꽭釉뚮��뒪�쓽 �룆由쎌슫�룞怨� �뒪肄뷀븘�뱶 援먯닔

2017· article· en· W6988462373 on OpenAlexaboutno aff

Bibliographic record

VenueYUHSpace (Yonsei University Medical Library) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSeveranceIndependence (probability theory)PoliticsGeopoliticsPopularityFront (military)
DOInot available

Abstract

fetched live from OpenAlex

This paper illuminates how a medical missionary and a missionary hospital are related to the independence movement in Korea. The missionary hospital was a medical and charitable institution, not a hotbed of politics and social movement. However, as a missionary medical center, Severance Hospital became the center of the Korean Independence Movement in the early 20th Century, and Professor Frank Schofield (1887-1970) played a crucial role. Several reasons underlie Severance Hospital`s focal position in the Korean Independence Movement. The first of these is geopolitical: Seoul station, situated in front of Severance Hospital, was the center of traffic for the whole country. Essentially, Seoul station was the gateway to Seoul. Because of this geopolitical factor, Severance Hospital served as the main stage for political history in Korea and saw movements such as the Korean Liberation in 1945, the Korean War, and the April 19th Revolution. A second reason why Severance Hospital was the base for the independence movement relates to its social history. The hospital had a tradition of inaugurating social and independence movements. Chejungwon, the first Western hospital and medical school in Korea, graduated many students from medical school. These graduates, and the medical school personnel who taught them, participated in missionary activity, social enlightenment, and the independence movement. A third factor enabling Severance Hospital to play a key role in the independence movement is connected to its leadership at the time. Horace Allen, Oliver Avison, and Oh Geung-sun, the heads of Chejungwon and Severance Hospital, organized the student Young Men`s Christian Association (YMCA) in Korea. Most students in Severance Medical College (SMC) joined the student YMCA, which networked with other branches throughout the whole country network. The branch at SMC carried out missionary and social work through this network. As the March 1st Independence Movement proceeded, the student YMCA at SMC was heavily involved in promoting the independence movement. Finally, the human network in Severance Hospital was pivotal in the independence movement. Many people, such as doctors, nurses, and other medical staff, stayed in the hospital. They communicated vital information with each other and passed down their personal experiences. This human network operated in Severance Hospital and throughout the country as a whole. Human networking was not a one-time event in the independence movement; it was a critical, on going factor. Professor Frank Schofield became the symbol of the human network. As the Severance Union Medical School (SUMC) started in 1913, the Canadian Presbyterian church decided to dispatch a bacteriologist, Professor Frank Schofield to SUMC. Over time, he came to be respected due to his upright character. He participated in YMCA activities and the human network in Severance Hospital, which led him to become a major player in the independence movement. As an ardent supporter of the struggle for independence from Japanese occupation, he made a photographic record of events, including the Suchonri and Jeamri massacres. He gathered information about independence fighters and campaigned for civil rights for prisoners. Throughout his life, he showed himself to be a practical and intellectual man.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.991
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.006
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0010.002
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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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