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Record W4392964418 · doi:10.1007/s10113-024-02215-6

Braided motivations for Iceland’s first wave of mass emigration to North America after the 1875 Askja eruption

2024· article· en· W4392964418 on OpenAlexaboutno aff
Ulf Büntgen, Ólafur Eggertsson, Clive Oppenheimer

Bibliographic record

VenueRegional Environmental Change · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsMass migrationEmigrationGeographyArchaeologyImmigration

Abstract

fetched live from OpenAlex

Abstract More than 14,000 Icelanders emigrated to North America between 1870 and 1914 CE. Mass movement from Iceland accelerated the year after the explosive eruption of Askja in 1875, and both contemporary and recent commentators have linked the two circumstances. Despite an abundant scholarship on Icelandic emigration in this period, the direct and indirect roles of the eruption as a possible stimulus remain unclear. Here, we engage critically with a range of contemporary source materials as well as meteorological and climatological information to re-assess where Askja fits into the picture of Iceland’s first wave of mass migration. We find that emigration was undoubtedly fuelled by the hardships of Icelanders and their growing contacts with countrymen already in the Americas, and that the highest proportions of emigrants came from counties most directly impacted by the Askja eruption. However, it also emerges that the eruption served as a lever for interested parties in Britain and Canada to persuade large numbers of desirable migrants to settle in North America. Our study highlights the opportunities that discrete episodes of volcanic activity present to probe the complex interrelationships of nature and society.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.043
GPT teacher head0.224
Teacher spread0.181 · 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 designQualitative
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

Citations2
Published2024
Admission routes1
Has abstractyes

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