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Record W2984998249 · doi:10.1111/cag.12576

Appreciating the heterogeneity in the unity of Africa: A socio‐ecological perspective on Africa's geographies

2019· article· en· W2984998249 on OpenAlexvenueno aff
Shuaib Lwasa

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsPoliticsDiversity (politics)ColonialismPovertyGeographySociologyPolitical economyDevelopment economicsPolitical scienceAnthropologyEconomics

Abstract

fetched live from OpenAlex

The African continent is known by various metaphors and geographies, but for many there are also unknowns about the continent. Geopolitically, Africa is a continent that is considered remote—an economically emerging continent seen as entangled in persistent challenges of wars, political dictatorship, poverty, disease, and more recently migration. Given these predispositions it is typical to stereotype events, practice, and behaviour as “African.” There is, however, now recognition of the continent as emerging economic power house. But unpacking the diversity of Africa reveals a huge potential with respect to resource endowments, diversity of ecology, socio‐cultural economic advancement, politics, language, and demographics. Colonial history coupled with traditional Africa shaped the geopolitical boundaries that have added to the confusion about this massive and diverse continent. Intellectual discourses either amplify the differences due to specificities of geographical focus or generalizations such as the contested notion of “African.” However, using socio‐ecological lenses, Africa is unified by these very differences in addition to being a massive landmass with several big and small island states. Appreciating these differences is useful to understanding the observed patterns of social, economic, and political systems that unify the continent. This paper illustrates the notion of “African” to describe the heterogeneous nature of a “unified” continent. Some illustrative examples between Africa and other continents are used.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0010.003
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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 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

Citations9
Published2019
Admission routes1
Has abstractyes

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