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Record W7112325063

Revealing a Hidden Cost: determining the public service cost of poverty in Ireland

2022· other· en· W7112325063 on OpenAlexaboutno aff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2022
Typeother
Languageen
FieldSocial Sciences
TopicSocial Issues and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyMeasuring povertyCost of livingIrishIdentification (biology)Public serviceBasic needsScale (ratio)Standard of living
DOInot available

Abstract

fetched live from OpenAlex

Living life on a poverty income is common in Irish society. Between 2010-20, on average one in seven people lived on an income below the poverty line – approximately 720,000 individuals. By necessity living life on such a low-income imposes costs on these individuals and families. Making ends meet involves personal sacrifices, restricts options and limits opportunities; and for many it is not always possible to find ways to make ends meet. These individual costs of poverty are large scale and leave effects that last years and at times generations. Alongside these individual costs, poverty is responsible for other costs. In particular, the presence of poverty in a society triggers demands on the public purse. These costs derive from the identification of poverty as a determining factor in the need for, and demand for, a wide range of public services and policies ranging across almost all areas of public policy. Building on past literature from the UK, USA, Canada and New Zealand this study attempts to establish a heretofore absent benchmark for the recurring annual costs to the state of poverty in Ireland. In doing so it adopts a different approach to the existing literature, drawing from experiences in the economic evaluation literature, to determine a range of costs rather than just one figure. These range from a conservative ‘low estimate’ to an upper-limit ‘high estimate’ with a ‘main estimate’ reflecting the most probable annual cost. The analysis is based on a review of €27.9 billion of annual public service expenditure and highlight for all members of society, whether above or below the poverty line, the recurring public expenditure costs incurred by society as a result of 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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.926
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.374
Teacher spread0.312 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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