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Record W2083680816 · doi:10.7202/1029368ar

Risquer sa vie pour sauver des âmes : les dangers de la conversion religieuse dans les premières missions en Livonie

2015· article· fr· W2083680816 on OpenAlexaffvenue
Louis Provost-Brien

Bibliographic record

VenueCahiers d histoire · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical Legal Studies and Society
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La mission chrétienne ne fut pas toujours tournée vers l’intégralité de l’Europe. On ne voulait à la base qu’évangéliser les peuples ayant appartenu à l’Empire romain. Cependant, il advint que le champ apostolique s’élargit, entre autres vers la Livonie au XIIe siècle. Conséquemment, il est justifié de se demander ce qui poussa les missionnaires à partir vers ces contrées. Pour expliquer ce phénomène, il faut d’abord définir les risques encourus par ceux-ci lors des missions, qu’ils soient environnementaux ou humains. Puis, il faut expliquer ce qui, dans l’évolution du christianisme, poussa ces hommes à évangéliser les autres.

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)0.006
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.009
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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