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Record W2937715188 · doi:10.5287/ora-am8mkokmd

The impact of international actors on domestic agricultural policy: a comparison of cocoa and rice in Ghana

2016· dissertation· en· W2937715188 on OpenAlexfundno aff
Jonas Heirman

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2016
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
FundersAlzheimer Society Research ProgramMinistry of Foreign Affairs
KeywordsAgricultureContext (archaeology)Agricultural policyCommodityFood securityFood policyGovernment (linguistics)Impact assessmentInternational relationsPolitical scienceForeign policyPoliticsEconomicsDevelopment economicsBusinessGeographyMarket economyPublic administration

Abstract

fetched live from OpenAlex

The global financial and food crisis of 2007 and 2008 was followed by a surge in foreign interest and investment in African agriculture. Renewed global interest in African agriculture was also accompanied by an increase in international efforts to influence domestic agricultural policies, including in Ghana. In the context of an increasingly globalised food regime and integrated commodity markets, this thesis answers the question: to what extent do international actors impact domestic agricultural policies in Ghana?<br><br>Policy ‘impact’ is understood as the marked influence that international actors have on policy goals and the resources, institutions, and knowledge used for achieving them. This thesis compares case studies of cocoa and rice policy over two different periods in Ghana’s recent history (1983-1995 and 2003-2012) to understand how international actors use their power and resources to impact agricultural policies. The comparison of cocoa and rice policy is used to address two gaps in existing literature by examining how the impact of international actors relates to: 1) the political economy for a specific crop; and 2) the interaction between actors at international, national and local levels. Findings from the comparative analysis are then used to test existing theories for how international actors influence government policy in Africa more generally. In particular, findings provide new insights into how the impact of international actors on African agricultural policies is strongly associated with the effect of policy decisions on the longer-term political economy for a particular crop.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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