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Record W4292513363 · doi:10.21203/rs.3.rs-1902681/v1

Missions, Fertility Transition, and the Reversal of Fortunes: Evidence from Border Discontinuities in the Emirates of Nigeria

2022· preprint· en· W4292513363 on OpenAlexaff
Dozie Okoye, Roland Pongou

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsUniversity of OttawaDalhousie University
Fundersnot available
KeywordsFertilityDemographic transitionGeographyPaceDevelopment economicsPopulationHuman capitalColonialismPer capitaEconomic growthGovernment (linguistics)Demographic economicsEconomicsPolitical scienceSociologyDemography

Abstract

fetched live from OpenAlex

Abstract What are the origins of differences in fertility and economic transition across African societies? This paper addresses this question by causally estimating average and heterogeneous effects of colonial-era Christian missions on human capital accumulation, fertility decline, and household wealth in Nigeria. Our identification strategy exploits discontinuities in mission stations around the borders of the Emirates of Northern Nigeria, where missionary activities were restricted by the colonial administration. We find that areas with greater historical missionary activities have higher levels of schooling, lower levels of fertility, and higher household wealth today. The long-run effect of missions is not found in areas with early access to government schools, and is larger for population subgroups—women and Muslims—that have historically suffered disadvantages in access to education. Importantly, we show that the restriction of missions from the Emirates of Northern Nigeria has led to a reversal of fortunes, wherein areas that were more prosperous and institutionally developed in the past are relatively poorer today. The analysis provides novel insights into the differential pace of demographic transition between Northern and Southern Nigeria, and highlights patterns consistent with the prediction of Unified Growth Theory, whereby an improved technological environment leads to greater demand for education, triggering a fertility decline, resulting in higher incomes per capita.JEL Classification: I20, N30, N37, N47, O15, Z12.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.168
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.439
Teacher spread0.321 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

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