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Climatic Choreography of Health and Disease

2017· book-chapter· en· W3098165504 on OpenAlexaboutno aff
Anthony J. McMichael

Bibliographic record

VenueOxford University Press eBooks · 2017
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyClimate changePopulationFlood mythEcologySocioeconomicsEnvironmental healthMedicineBiologySociology

Abstract

fetched live from OpenAlex

Ever Since Humans First looked to the skies for relief, the changing mood of the climate has been assumed to be beyond human control, other than through supplication, ceremony, and ritual sacrifice. In secu­lar modern times, there has been little interest in studying climatic influ­ences on patterns of disease and survival. After all, we can curb cigarette smoking, but we cannot change the climate. Or so we thought. Now, though, there is new interest in understanding how human- driven cli­mate change affects human health, in the present and into the future. The risks to human health extend far beyond the well- known dangers from heat extremes, fires, floods, and mosquito proliferation, as signaled in Chapter 1. Changes in regional climates influence crop yields and livestock productivity and hence the occurrence of hunger, undernutri­tion, and stunted child development; they affect the ranges, seasonality, and rates of many infectious diseases. Heightened extremes of weather precipitate cholera outbreaks in impoverished crowded communities and, given the often destructive impacts of many events, can result in post- traumatic stress, long- term depression, and survivor guilt. The list goes on. There are both physical and mental health conse­quences of rural droughts and climate- exacerbated population displace­ment, migration, and resource conflicts. In the Canadian and Alaskan Arctic region, where 2°C warming has already occurred since 1950, the loss of coastal sea ice and permafrost is disrupting traditional Inuit hunting routines. Without access to prey species such as seals and cari­bou, physical activity levels have decreased and the population’s reliance on imported energy- dense processed foods has increased. Rising levels of obesity, cardiovascular disease, and type II diabetes have been the result. As climate change tightens its grip in coming decades, an increasing portion of all adverse health impacts is likely to result from indirect ef­fects such as reduced food yields, depleted freshwater supplies, and loss of the physical protection provided by reefs, mangroves, and forests. In the past, moderately warmer periods in particular regions, spanning several centuries, often enhanced crop yields and population growth.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.059
GPT teacher head0.259
Teacher spread0.200 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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
Published2017
Admission routes1
Has abstractyes

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