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Record W3170567434 · doi:10.14430/arctic72709

Food, Mobility, and Health in a 17th and 18th Century Arctic Mining Population in Silbojokk, Swedish Sápmi

2021· article· en· W3170567434 on OpenAlexvenueno aff
Markus Fjellström, Åsa Lindgren, Olalla López‐Costas, Gunilla Eriksson, Kerstin Lidén

Bibliographic record

VenueARCTIC · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersXunta de GaliciaStockholms UniversitetKnut och Alice Wallenbergs Stiftelse
KeywordsArcticThe arcticGeographyPopulationδ13CEnvironmental healthIsotope analysisDemographyMedicineBiologyEcologySociologyStable isotope ratio

Abstract

fetched live from OpenAlex

Established in 1635, the silver mine of Nasafjäll and the smeltery site in Silbojokk in Swedish Sápmi were used during several phases until the late 19th century. Excavations in Silbojokk, c. 40 km from Nasafjäll, have revealed buildings such as a smeltery, living houses, a bakery, and a church with a churchyard. From the beginning, both local and non-local individuals worked at the mine and the smeltery. Non-locals were recruited to work in the mine and at the smeltery, and the local Sámi population was recruited to transport the silver down to the Swedish coast. Females, males, and children of different ages were represented among the individuals buried at the churchyard in Silbojokk, which was used between c. 1635 and 1770. Here we study diet, mobility, and exposure to lead (Pb) in the smeltery workers, the miners, and the local population. By employing isotopic analysis, δ13C, δ15N, δ34S, 87Sr/86Sr and elemental analysis, we demonstrate that individuals in Silbojokk had a homogenous diet, except for two individuals. In addition, both local and non-local individuals were all exposed to Pb, which in some cases could have been harmful to their health.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

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

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 head0.055
GPT teacher head0.381
Teacher spread0.326 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2021
Admission routes1
Has abstractyes

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