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Record W132677935 · doi:10.15173/nexus.v21i1.213

Health and morbidity in ancient Chilean populations: Preliminary perspectives using subadult data

2009· article· en· W132677935 on OpenAlexaffvenue
Christine E Boston

Bibliographic record

VenueNEXUS The Canadian Student Journal of Anthropology · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsSubsistence agricultureBioarchaeologyGeographyFishingAgriculturePrehistoryDemographySocioeconomicsEthnologyHistoryEcologyArchaeologyBiologySociology

Abstract

fetched live from OpenAlex

Bioarchaeological studies have suggested a general trend whereby the health of past populations degraded as they transitioned from a nomadic, hunter-gatherer lifestyle to a sedentary, agricultural lifestyle. Ancient societies of northern Chile provide a unique perspective on this debate in that while the earliest societies relied on hunting and gathering they were at the same time sedentary. Furthermore, later agricultural Chilean societies had relatively balanced diets since they also relied on fishing. Thus, this study examined four skeletal markers of health on sixty-one subadults ranging from the Archaic (7000-1000 B.C.) to Late Horizon (A.D. 1476-1532) periods in order to prove the impact of subsistence strategies and social organization on individuals’ health. These health markers were cribra orbitalia and porotic hyperostosis, trauma, dental pathological conditions, and infections. Despite the small sample size, this study gives a glimpse of childhood health conditions and morbidity patterns in northern Chile. The results showed no statistical differences of morbidity patterns between preagricultural and agricultural societies, a contradiction to previous assumptions about morbidity differences between preagricultural and agricultural societies.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score1.000

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 studies0.0010.012
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 head0.121
GPT teacher head0.375
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2009
Admission routes2
Has abstractyes

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