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Record W3092885275

Household resilience against food Insecurity in areas of protracted conflicts: a Libyan study.

2019· dissertation· en· W3092885275 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNottingham Trent University's Institutional Repository (Nottingham Trent Repository) · 2019
Typedissertation
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsFood securityLivelihoodSocial capitalPsychological resilienceDevelopment economicsNatural capitalFood insecurityCoping (psychology)Economic growthPovertyBusinessGeographyPolitical scienceSocioeconomicsEconomicsPsychologyAgricultureSocial psychologyEcosystem services
DOInot available

Abstract

fetched live from OpenAlex

Recent estimates provided by UN institutions indicate that over 820 million people are currently suffering from food insecurity worldwide. Conflict has been widely identified as one of the key causes of such persistent and high level of global food insecurity, particularly in the Middle East and North African (MENA) region, including Libya. It is, therefore, important to know how to overcome this problem. Recently, ‘resilience-building’ has been identified by many development institutions around the world as a strategy to improve food security in conflict-affected areas. However, little was empirically known what makes households resilient against food insecurity in areas of protracted conflicts. In this thesis, I explored this question based on research in Libya.
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\nDrawing on a range of literature, especially the Sustainable Livelihoods literature, I developed an analytical framework. In this framework, resilience was defined as the ability of a household to maintain an appropriate level of food consumption (access) during conflict times. It was proposed that this ability to be resilient would depend on nine factors: exposure-sensitivity to conflicts, five types of assets (natural capital, physical capital, financial capital, human capital and social capital), coping strategies, access to basic services (ABS), and social safety nets (SSN).
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\nA mixed-methods approach was used in the research. Data were collected through two phases – a qualitative phase and a quantitative phase. The purpose of the qualitative phase was to understand the contexts in Libya, including the nature of the conflicts and its effects on household food security; the nature of assets important in Libyan context; the strategies households used to cope with conflicts and food insecurity; and the nature of the ABS and SSNs relevant to Libya. For this, data were gathered through 55 semi-structured interviews as well as field observations and conversations. The data were analysed qualitatively using the NVivo software.
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\nThe findings from the qualitative phase were then fed into the design of the quantitive part of the research. In the quantitative phase, survey data were collected from a sample of 320 households. A structured questionnaire was used in data collection. The questionnaire data were analysed using the software SPSS versions 25 and 26. Food security was measured using the Food Consumption Score (FCS) and the Household Food InsecurityAccess Scale (HFIAS). Index scores were created for both FCS and HFIAS according to the guideline in the literature. For the nine explanatory variables, index scores were also created using descriptive statistics and Principal Component Analysis. To determine the effects of these nine explanatory variables on food insecurity resilience, binary logistics regression analyses were performed.
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\nResults from both the qualitative and quantitative phase confirmed a significant decline in households’ food security during conflict times, compared to the pre-conflict times. The result of the qualitative phase suggested that all the factors in the proposed analytical framework were important for household food security. However, quantitative analyses showed that only social capital at time t (pre-conflict) had a statistically significant positive effect on resilience against food insecurity during the major conflict in 2011 (time t+1). To analyse resilience in time t+2, two logistic models were created – effects of the nine explanatory variables that households possessed in time t, and time t+1. The results of the first model indicated that household natural capital in time t had a significant positive effect on resilience in time t+2. The result of the second model indicated that household resilience in time t+2 was significantly affected by three variables – natural capital, financial capital and social capital in time t+1. Most of these significant effects were, however, found in the models in which food security was measured as FCSs.
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\nThe main conclusion of this research is that assets play important roles in household food security resilience. The findings also lead to the conclusion that the type of assets that can affect household resilience also depends on which conflict time is taken into analysis and how the variable “food (in)security” is measured. These suggest that, for resilience building in areas of protracted conflict, it is important to identify which assets are important. Development agencies and institutions should then focus on protecting and improving those assets. It is also important for developing agencies to use appropriate tools for assessing and monitoring “food (in)security”, since the results may be different based on which tools are used.

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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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.004
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 head0.066
GPT teacher head0.347
Teacher spread0.281 · 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