MétaCan
Menu
Back to cohort
Record W3087815667 · doi:10.3390/ijerph17207555

Bleeding Bodies, Untrustworthy Bodies: A Social Constructionist Approach to Health and Wellbeing of Young People in Kenya

2020· article· en· W3087815667 on OpenAlexaff
Elizabeth Opiyo Onyango, Susan J. Elliott

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFocus groupThematic analysisFeelingKenyaPsychologyConstruct (python library)SociologyQualitative researchPolitical scienceSocial psychologySocial science

Abstract

fetched live from OpenAlex

The Sustainable Development Goals provide a global development agenda that is meant to be inclusive of all people. However, the development needs for vulnerable populations such as youth are not reflected within the policy agenda of some developing countries. One of the reasons for this is that research that explores health and wellbeing concerns for young people are sparse in the region and where they exist, the focus has been on marginalized subgroups. To address this gap, this cross-sectional study explored the health and wellbeing of youth in Kenya. We conducted 10 focus group discussions and 14 in-depth interviews with youth ages 15 to 24 years. A thematic analysis of the data revealed that structural factors are important influencers of youth perceptions and their social constructions of health and wellbeing. Kenyan youth are concerned about the health status and healthcare services in their communities, as well as issues of community trust of youths and perceived risks of political misuse and emotional suffering. Our findings suggest that youth transitioning into adulthood in resource-constrained areas experience feelings of powerlessness and inability to take charge over their own life. This impacts how they perceive and socially construct health and wellbeing.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.079
GPT teacher head0.388
Teacher spread0.308 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicYouth Education and Societal DynamicsFrench-language works237,207