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Record W35705361 · doi:10.1136/jech-2021-217202

Analisis Tingkat Kepuasan Ke CV Banyu Biru, Kebayoran Lama, Jakarta Selatan.

2001· dissertation· en· W35705361 on OpenAlexfundno aff
Cucu Rukoyah

Bibliographic record

VenueJournal of epidemiology and community health · 2001
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsGeography

Abstract

fetched live from OpenAlex

Although the theory and methods of legal epidemiology-the scientific study and deployment of law as a factor in the cause, distribution, and prevention of disease and injury in a population-have been well developed in the context of domestic law, the challenges posed by shifting the frame of analysis to the global legal space have not yet been fully explored. While legal epidemiology rests on the foundational principles that law acts as an intervention, that law can be an object of scientific study and that law has impacts that should be evaluated, its application to the global level requires the recognition that international laws, policies and norms can cause effects independently from their legal implementation within countries. The global legal space blurs distinctions between 'hard' and 'soft' law, often operating through pathways of global agenda setting, legal language, political pressures, social mobilisation and trade pressures to have direct impacts on people, places and products. Despite these complexities, international law has been overwhelmingly studied as operating solely through national policy change, with only one global quasi-experimental evaluation of an international law's impact on health published to date. To promote greater adoption of global legal epidemiology, we expand on an existing typology of public health law studies with examples of policymaking, mapping, implementation, intervention and mechanism studies. Global legal epidemiology holds great promise as a way to produce rigorous and impactful research on the international laws, policies and norms that shape our collective health, equity and well-being.

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)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.103
GPT teacher head0.339
Teacher spread0.236 · 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.

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

Citations0
Published2001
Admission routes1
Has abstractyes

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