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Record W4327621905 · doi:10.1080/13676261.2023.2187282

Past, present and future: multiple motivations for youth’s financial and in-kind support to others in rural Ghana

2023· article· en· W4327621905 on OpenAlexfundno aff
Anne L. Buffardi, Victoria Ampiah, Nathaniel Amoh Boateng

Bibliographic record

VenueJournal of Youth Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersMastercard Foundation
KeywordsTypologyDichotomyAltruism (biology)Situational ethicsSociologyYouth studiesGender studiesSocial psychologyPsychology

Abstract

fetched live from OpenAlex

In the growing literature on youth transitions, comparatively little attention has been paid to the role that young people play as providers, particularly support for people outside of a nuclear family unit. Based on 92 interviews with 44 young adults living in rural Ghana, this research investigates the multiple reasons why they provide financial and in-kind support to a range of immediate, extended and non-family members. We create a typology of motivations, identifying eight reasons youth identified for supporting people across four generations. These drivers of support relate to the past, present and future and do not fall neatly into dichotomies of self-interest or altruism. Some are situational, dependent on the need of the recipient, the ability of the young person to provide support at that point in time and/or circumstances of other people in their broader family and social networks. Youth identified multiple reasons for supporting the same person and articulated different motivations depending on their relationship to the recipient and their gender. Together, these nuanced explanations offer insights into an often-overlooked aspect of youth transitions and a departure point for further research into the important role young people play in supporting others in their families and communities.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.358
Teacher spread0.294 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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