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Record W2463016702

[Axel Laurent-Christensen: a doctor "with feeling for snow"].

2001· article· en· W2463016702 on OpenAlexaboutno aff
B Harvald, Katherine Mccord

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerFeelingArcticHealth careThe arcticService (business)Health servicesMedicineFamily medicinePolitical scienceGeographyBusinessPsychologyEnvironmental healthArchaeologyLaw
DOInot available

Abstract

fetched live from OpenAlex

In 1950 the district medical officer of Qaqortoq/Julianehåb, Axel Laurent-Christensen retired after having served in this position since 1930. Afterwards, during the years 1950-55, he was a medical officer in Aklavik, NWT, Canada. Here he had the opportunity to compare the arctic Canadian health care with the Greenland health care system. In his diary, of which selected parts are given in the present paper, he has commented on the differences. In the 1950's the Canadian system was highly centralized with the well-equipped Charles Camsell Indian Hospital in Edmonton as the center. The Greenland health service, on the other hand, was decentralized, based on small surgically staffed peripheral hospitals. The development of these two health care systems during the past 50 years has accentuated these differences. Estimated by the infant mortality, the efficiency of the Greenland health care system was superior to the Canadian during the 1950's, whereas in the 1990's, the Canadian health service is vastly superior.

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)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.082
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0630.026

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 head0.095
GPT teacher head0.376
Teacher spread0.282 · 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
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
Published2001
Admission routes1
Has abstractyes

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