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Record W2591850731

Macroeconomic determinants of Emigration from Kenya

2016· preprint· en· W2591850731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMPRA Paper · 2016
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationKenyaAttractivenessDemographic economicsInflation (cosmology)EconomicsDestinationsPopulationPer capitaOvertimeExchange rateGeographyGravity model of tradeDevelopment economicsTourismLabour economicsDemographyPolitical scienceInternational economicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

The study examined the economic determinants of migration from Kenya to USA, Canada, Australia, Germany and United Kingdom by applying a unilateral migration gravity model during the period 2000-2015.The study applied the Least Square Dummy Variable specification technique to estimate the gravity model. The pull factors from Kenya were high inflation, exchange rate appreciation, high population and a rise in Kenyan GDP per capita.In considering the relative attractiveness of the destination countries in increasing order the finding showed Australia, Canada, UK and Germany were the prominent migration destinations. When emigration was considered overtime there was generally a positive trend except for 2007.Finallythe findings showed that if all the macroeconomic factors were held constant there will be a significant decline in migration from Kenya thus we conclude that besides other factors influencing migration, economic factors play a key role too.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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