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Record W2605833420 · doi:10.5539/ass.v13n5p57

Poverty Alleviation through Empowerment with a Focus on Partnership: A Case Study of Iran

2017· article· en· W2605833420 on OpenAlexvenueno aff
Hamid Sajadi, Salman Sadeghizadeh, Masoumeh Taghizadeh

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentGeneral partnershipPovertySnowball samplingAccountabilityPopulationPublic relationsSample (material)Economic growthBusinessSociologyPolitical scienceEconomicsMedicine

Abstract

fetched live from OpenAlex

Empowerment in the area of poverty alleviation, beyond being a partnership for improvement or progress of the performance, means accountability for the prioritized needs. As to empowerment, the approaches are mostly confined to motivational level or organizational and institutional reform. Based on this general approach, Iran has also drawn up many empowerment programs and implemented them through Imam Khomeini Relief Foundation (IKRF), the main supporting organization of the country. Pursuing the empowerment projects on the basis of this limited approach has been the source of instability for such projects. Evaluating the empowerment projects of Iran focused on poverty alleviation, developed and embedded in the broad programs of the IKRF, the study aims to identify the components of a pattern of empowerment for poverty alleviation through a social approach. Finally the proposed strategies are formulated based on three centers of active participation of the poor, strengthening inter-organizational relationships and defining an advisory role for supporting organizations to decision-making bodies. The methodology was descriptive-analytical and the data collected through direct observation and interviews with experts and academic elites and collecting questionnaires. Delphi Questionnaire was filled by the sample population in two categories of managers and experts of the IKRF and the clients. The Snowball technique was applied for identifying the size of the sample. The research questions were responded through SWOT analysis.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score1.000

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 studies0.0080.000
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 head0.159
GPT teacher head0.489
Teacher spread0.330 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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