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Record W4280493521 · doi:10.5430/ijba.v13n3p45

From Margins to Centre: Relocating Youth Participation in Radical Politics of International Development

2022· article· en· W4280493521 on OpenAlexvenueno aff
Gamel Abdul-Nasser Salifu

Bibliographic record

VenueInternational Journal of Business Administration · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionGrassrootsBlueprintPoliticsPublic relationsEconomic growthSociologyPolitical scienceEconomicsPsychologyLaw

Abstract

fetched live from OpenAlex

This paper focuses on youth participation in decision-making processes for economic growth and development. Very little is known of the effectivity of rural youth participation in the developing world. Drawing on recent empirical evidence of youth participation in economics and development research, the paper identifies the growing interest of policy makers on shorthanded interventions aimed at improving young lives. Going beyond official blueprints and the stated objectives of international development interventions, interventions have widely emphasized the mechanical aspects of projects rather than the direct impact of interventions on young beneficiaries. Understanding this is critical for development as recent projects’ high rate of failure and unintended consequences for beneficiaries continue to grow. Based on the review of over 100 documented cases of youth participation in Africa, Asia and Latin America, the paper offers a conceptual guide, reinforced by methodological suggestions for studying the representational ‘afterlives’ of development interventions. Inspired by the phenomenological works of economic development research, the paper recognizes young voices as repositories of non-hegemonic knowledge with the ability to creatively re-appropriate development legacies. While such conclusions may have been kept under relative control, they come to fore upon the termination of interventions. A grassroots-based approach aimed at studying post-intervention communities would reveal the palimpsest-like multilayers of flagship programmes across the developing world.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.027
Scholarly communication0.0120.009
Open science0.0010.019
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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