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Record W7074665417

On Poverty and Its Eradication

2024· book· en· W7074665417 on OpenAlexfundno aff

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2024
Typebook
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
FundersNational Social Science Fund of ChinaMinjiang UniversityYork University
KeywordsPovertyPandemicInequalityHuman Development ReportCoronavirus disease 2019 (COVID-19)Human development (humanity)
DOInot available

Abstract

fetched live from OpenAlex

Today the world observes the International Day for the Eradication of Poverty, first commemorated in Paris in 1987 and subsequently receiving official designation by the United Nations. It is a day for renewing commitment to the human project – to enable universal human development, making it possible for all humans to achieve their highest potential – and to reflect on poverty, how it thwarts human development, and how it might disappear. The challenge is not new, but it achieves new urgency as we start to emerge from the COVID-19 pandemic and realize that the damage it caused, to well-being and human development, was deeply intensified by poverty. This volume aims for accelerated growth of knowledge about poverty, its causes and consequences, its links to crises and disasters, its connections to inequality and fairness, the direction and speed of its trajectory in different contexts, and strategies for reducing it and their assessment.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.612
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.018
GPT teacher head0.265
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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