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Ecosystem approach to health: the integration of work and the environment

2012· article· en· W1516221195 on OpenAlexfundno aff
Maria Luiza de Jesus Lawinsky, Frédéric Mertens, Carlos José Sousa Passos, Renata Távora

Bibliographic record

VenueSocial medicine · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsExternalityPovertyUnemploymentUrbanizationPublic healthGoods and servicesSociologyEnvironmental ethicsEconomic growthEconomicsEcologyMedicineBiologyEconomy

Abstract

fetched live from OpenAlex

The dissociation of humans from nature results from the hegemony of capitalism and is expressed in the way most humans interact with their environment. This dissociation has produced imbalances that are expressed in the health of both humans and the environment. They arise from the divorce between “civilization” and the environment that sustains it and are seen in the mindless and unsustainable exploitation of natural resources for the production of material goods. Both productive activities and their negative externalities (pollution, climate change, unemployment, labor exploitation, unplanned urbanization, poverty, etc.) have serious health consequences for rural and urban environments. The concept of environmental health presented in this paper incorporates the relations between environmental and human health, aiming to foster more systematic studies of the interconnections between environmental risk factors (such as exposure to specific physical and chemical agents) and human diseases and public health. We understand health as a process determined by a complex web of biological, social, and psychological factors that develop within a defined geographical area. Assuming health to be a state of complete physiological and psychological wellbeing, it becomes clear that the major problems facing humanity today arise from the modern relationship between man and nature. The social welfare approach to health problems prevalent since the 19th century has not kept pace with our growing health problems. The study of occupational diseases caused by polluted workplaces has brought about a return to the old paradigm of preventing disease by promoting a healthy environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.186

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 studies0.0000.000
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 head0.108
GPT teacher head0.332
Teacher spread0.223 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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