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Record W2991536008 · doi:10.5539/jsd.v12n6p121

Gendered Sociocultural Structures and Africa’s Quest for Development

2019· article· en· W2991536008 on OpenAlexvenueno aff
Grace Reuben Etuk, Ugo Samuel Bassey, Ejukwa Osam

Bibliographic record

VenueJournal of Sustainable Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsGender mainstreamingEmpowermentPaceInequalitySociocultural evolutionEconomic growthSociologyMillennium Development GoalsPovertyPolitical scienceDevelopment economicsGender equalityGender studiesEconomicsGeography

Abstract

fetched live from OpenAlex

The way gender interfaces with development is a concern that has occupied the attention of development planners and feminists for some time now. The impetus for this concern is the realization that a key component for achieving development in all its dimensions is the existence of gender equality. This explains why the United Nations’ Millennium Development Goals of 2000 framed its third goal as “To promote gender equality and women empowerment”; and more recently in its Sustainable Development Goals of 2015, the fifth goal is “To achieve gender equality and empower all women and girls”. Against this backdrop, therefore, this paper attempts to accentuate the extent of gender inequality that has persisted in Africa’s social structures, and how it has so far affected development on the continent. Particular prominence is given to the ways gender inequality in Africa’s social structures have functioned to keep the continent’s development rate at a snail pace by crippling the extent of participation in the development process by women – the main victims of gender inequality. The issue of gender and its effects on Africa’s social systems and subsequently the processes that will lead up the continent’s development must be properly addressed if a highway is to be created for development to ride in Africa. Thus, among other recommendations, the paper advocates for gender mainstreaming in policies and programmes at country level on the continent.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.273
Teacher spread0.255 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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