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Rural ‘Community’, Chiefs and Social Capital: The Case of Southern Ghana

2007· article· en· W2135652798 on OpenAlexaff
Jeff Grischow

Bibliographic record

VenueJournal of Agrarian Change · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSocial capitalSociologyInequalityCohesion (chemistry)Promotion (chess)Political economySocial inequalityCommunity developmentCapital (architecture)Perspective (graphical)Economic growthDevelopment economicsPolitical scienceSocial scienceEconomicsLawGeography

Abstract

fetched live from OpenAlex

Social capital emphasizes community and social cohesion as the foundation of development. In Africa, this has prompted the promotion of traditional authorities as agents of development because chiefs and elders are assumed to embody communal norms. Critics have argued that this vision is ahistorical. In response, social capitalists have attempted to ‘historicize’ their analyses. But in many cases, ‘history’ simply refers to the micro‐level production of trust, networks and norms. From a historian's perspective this is problematic because it ignores historical processes that often produce social hierarchies and inequality within ‘traditional’ communities. Using a case study from southern Ghana, I argue that, because of their particular view of history, many social capitalists remain blind to differentiation and conflict at the community level. As a result, social capital‐driven projects run the risk of reproducing deeply rooted inequalities.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.006
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.245
Teacher spread0.189 · 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 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

Citations69
Published2007
Admission routes1
Has abstractyes

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