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Record W3122374283

Social Isolation and its Relationship to Multidimensional Poverty

2014· preprint· en· W3122374283 on OpenAlexaboutno aff
Kim Samuel, Sabina Alkire, John Hammock, China Mills, Diego Zavaleta

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2014
Typepreprint
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPovertySocial connectednessSocial isolationCulture of povertyIsolation (microbiology)EmpowermentDimension (graph theory)Development economicsSocial securitySocial protectionEconomic growthPolitical scienceSociologyBasic needsEconomicsPsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

While the multidimensionality of poverty is well-recognised, one dimension of poverty which has been often overlooked is weak social connectedness. This paper draws on conceptual, participatory and measurement literatures to show that social connectedness appears to be an important missing ingredient of multidimensional poverty analyses, with social isolation being a feature which exacerbates the condition of poor persons. To provide contextual detail as to its impact on persons in marginalized communities, we present qualitative primary data from South Africa and Mozambique and review pertinent studies of the First Nations of Canada and among persons with disability. A policy challenge for social isolation is that it is often seen as stemming from an individuals’ capacity rather than resulting from the broader social context. The closing section outlines areas for policy. \n \nThe study of multidimensional poverty has enlarged the range of factors which are considered part of impoverishment. For example, the Commission on Global Poverty Measurement led by Tony Atkinson proposed that physical security from violence be regularly monitored by the World Bank as a non-monetary dimension of poverty (World Bank, 2016). We argue in this paper that social isolation and decreased social connectedness can be important results of living in poverty, are themselves an aspect of poverty, and are also contributory factors to the persistence of poverty; consequently, they merit more extensive analysis than they often receive. This paper aims to catalyse that analysis by drawing together literature, case studies illuminating social isolation in different contexts, and observations of policy responses, in order to suggest how appropriate analyses of social isolation can meet a deeply human demand and improve policy design. \n \nSynthesising a dispersed literature, we first examine how social isolation fits into multidimensional poverty conceptually. We then discuss primary field research from South Africa and Mozambique which reveals the influence of social isolation in the lived experience of poverty from the perspective of the impoverished themselves. The next section draws on documented histories of the Aboriginal peoples of Canada to investigate how isolation – in residential schools – created long-term impacts on poverty and isolation. Finally, drawing on the discussion on incorporating people with disabilities, we explore how reducing social isolation, through programmes aimed at reintegrating people with disabilities into their communities, can provide insight into directions for policy. In concluding, we show how addressing the issue of social isolation in a concerted fashion while recognizing that it arises in diverse contexts can potentially mitigate poverty.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.007
Scholarly communication0.0020.002
Open science0.0000.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.166
GPT teacher head0.400
Teacher spread0.234 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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