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Record W4289262561 · doi:10.1073/pnas.2122854119

International treaties have mostly failed to produce their intended effects

2022· review· en· W4289262561 on OpenAlexafffund
Steven J. Hoffman, Prativa Baral, Susan Rogers Van Katwyk, Lathika Sritharan, Matthew Hughsam, Harkanwal Randhawa, Gigi Lin, Sophie Campbell, Brooke Campus, Maria Dantas, Neda Foroughian, Gaëlle Groux, Elliot Gunn, Gordon Guyatt, Roojin Habibi, Mina Karabit, Aneesh Karir, Krista Kruja, John N. Lavis, Olivia Lee, Binxi Li, Ranjana Nagi, Kiyuri Naicker, John‐Arne Røttingen, Nicola Sahar, Archita Srivastava, Ali Tejpar, Maxwell Tran, Yuqing Zhang, Qi Zhou, Mathieu J. P. Poirier

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2022
Typereview
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsImpactCentre for Global Health ResearchMcMaster UniversityYork University
FundersOntario Ministry of Economic Development, Job Creation and TradeCanadian Institutes of Health ResearchNorges ForskningsrådGovernment of Canada
KeywordsEnforcementTreatyNormativePolitical scienceInternational lawBusinessInternational tradeLaw and economicsLawEconomics

Abstract

fetched live from OpenAlex

There are over 250,000 international treaties that aim to foster global cooperation. But are treaties actually helpful for addressing global challenges? This systematic field-wide evidence synthesis of 224 primary studies and meta-analysis of the higher-quality 82 studies finds treaties have mostly failed to produce their intended effects. The only exceptions are treaties governing international trade and finance, which consistently produced intended effects. We also found evidence that impactful treaties achieve their effects through socialization and normative processes rather than longer-term legal processes and that enforcement mechanisms are the only modifiable treaty design choice with the potential to improve the effectiveness of treaties governing environmental, human rights, humanitarian, maritime, and security policy domains. This evidence synthesis raises doubts about the value of international treaties that neither regulate trade or finance nor contain enforcement mechanisms.

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)0.082
metaresearch head score (Gemma)0.230
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.082
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0820.230
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0080.010
Science and technology studies0.0010.005
Scholarly communication0.0080.006
Open science0.0030.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0200.002

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 head0.107
GPT teacher head0.391
Teacher spread0.284 · 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 designObservational
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

Citations99
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicInternational Development and AidFrench-language works237,207