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Record W2592906613

Public goods and ethnocultural diversity: A case of Nigeria

2016· dissertation· en· W2592906613 on OpenAlexaboutno aff
Mateusz Gwozdz

Bibliographic record

VenueMurdoch Research Repository (Murdoch University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Circumstantial evidencePoliticsMulticulturalismIdeologyCultural diversityEthnic groupPolitical scienceState (computer science)Political economyRace (biology)Development economicsSociologyGender studiesLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

Ethnic and other cultural diversity has become something of an ideological holy of holies in Western societies. However, in spite of idealistic shibboleths surrounding the concept, academic literature broadly supports the contention that ethnocultural diversity is negatively correlated with public goods provision, political stability, economic growth and the like. As such, a broad reexamination of diversity’s inherent desirability is necessary. This paper takes a two-pronged approach by conducting a critical review of relevant literature, and cross-referencing it with the case study of Nigeria. Whilst multicultural “settler societies” such as the USA or Canada boast a number of fundamental differences to postcolonial, “primordially” diverse societies such as Nigeria, the latter nonetheless offers a number of generalizable lessons which can be broadly applied to Western statecraft and policy making as well. Broadly speaking, an analysis of Nigeria provides considerable circumstantial evidence to support the academic consensus on ethnocultural diversity, and allows one to conceptually link big-picture, longitudinal studies with micro-level studies. At the same time, it provides considerable nuance to those broad conclusions, indicating that even though ethnocultural diversity is broadly correlated with lower levels of public goods provision, precise causes for this state of affairs tend to differ and diversity is far from the be-all, end-all of political instability, low levels of development and the like.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.433
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.142
GPT teacher head0.357
Teacher spread0.215 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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