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Record W4390500562 · doi:10.1186/s12889-023-17408-7

Associations between child marriage and food insecurity in Zimbabwe: a participatory mixed methods study

2024· article· en· W4390500562 on OpenAlexfundno aff
Katherine Gambir, Abel Blessing Matsika, Anna Panagiotou, Eleanor Snowden, Clare Lofthouse, Janna Metzler

Bibliographic record

VenueBMC Public Health · 2024
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsMedicineBiostatisticsPublic healthEnvironmental healthFood insecurityEpidemiologyMultimethodologyFood securityNursingSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Child marriage is a global crisis underpinned by gender inequality and discrimination against girls. A small evidence base suggests that food insecurity crises can be both a driver and a consequence of child marriage. However, these linkages are still ambiguous. This paper aims to understand how food insecurity influences child marriage practices in Chiredzi, Zimbabwe. METHODS: Mixed methods, including participant-led storytelling via SenseMaker® and key informant interviews, were employed to examine the relationship between food insecurity and child marriage within a broader context of gender and socio-economic inequality. We explored the extent to which food insecurity elevates adolescent girls' risk of child marriage; and how food insecurity influences child marriage decision-making among caregivers and adolescents. Key patterns that were generated by SenseMaker participants' interpretations of their own stories were visually identified in the meta-data, and then further analyzed. Semi-structured guides were used to facilitate key informant interviews. Interviews were audio-recorded, and transcribed and translated to English, then imported into NVivo for coding and thematic analysis. RESULTS: A total of 1,668 community members participated in SenseMaker data collection, while 22 staff participated in interviews. Overall, we found that food insecurity was a primary concern among community members. Food insecurity was found to be among the contextual factors of deprivation that influenced parents' and adolescent girls' decision making around child marriage. Parents often forced their daughters into marriage to relieve the household economic burden. At the same time, adolescents are initiating their own marriages due to limited alternative survival opportunities and within the restraints imposed by food insecurity, poverty, abuse in the home, and parental migration. COVID-19 and climate hazards exacerbated food insecurity and child marriage, while education may act as a modifier that reduces girls' risk of marriage. CONCLUSIONS: Our exploration of the associations between food insecurity and child marriage suggest that child marriage programming in humanitarian settings should be community-led and gender transformative to address the gender inequality that underpins child marriage and address the needs and priorities of adolescent girls. Further, programming must be responsive to the diverse risks and realities that adolescents face to address the intersecting levels of deprivation and elevate the capacities of adolescent girls, their families, and communities to prevent child marriage in food insecure settings.

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)0.007
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 score0.016
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.438
Teacher spread0.320 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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