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Record W2770918875 · doi:10.3968/9938

Study on Social Organizations’ Role During the Process of Antipoverty in Argentina

2017· article· en· W2770918875 on OpenAlexvenueno aff
Rong Tan, Yanan Li

Bibliographic record

VenueCross-cultural communication · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American socio-political dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyUnemploymentGovernment (linguistics)Independence (probability theory)PopulationEconomic growthMiddle classComplementarity (molecular biology)Political scienceCulture of povertyDevelopment economicsSociologyEconomicsBasic needsLaw

Abstract

fetched live from OpenAlex

From 1970s to the beginning of 1990s, Argentina had experienced a rapid process of immiserization which led to the increase of unemployment and the reduction of income. During the period from 1990s to the beginning of 21st century, “poverty relapse” once again, both the absolute poverty population and the relative poverty population have increased exponentially, and then here came a new poor class which consisted of the middle class. During this process, social organizations in Argentina engaged in the labor training progress and economic development plan which were proposed by the government, playing the role of employment assistance in the process of antipoverty, from charity relief to technical assistance, from disorder to professionalize progress focusing on organization ability construction, from independence to collaboration and complementarity with government. Social organizations have made up the deficiency of the market mechanism and inadequacies of government poverty alleviation work, which have accumulated rich experience, and social organizations become an important force of antipoverty in Argentina.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.407
Teacher spread0.378 · 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
Published2017
Admission routes1
Has abstractyes

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