MétaCan
Menu
Back to cohort
Record W2896347717 · doi:10.1093/ser/mwy038

Is social investment inimical to the poor?

2018· article· en· W2896347717 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSocio-Economic Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInvestment (military)EconomicsWelfare stateWelfarePoliticsSocial protectionSocial WelfareState (computer science)Public economicsLabour economicsEconomic policyMarket economyEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Abstract In the last two decades, the social investment strategy has been the main approach to welfare state reform. Concretely, two spending programs have dominated the agenda: the expansion of active labor market programs and the development of childcare services. Many authors have suspected, however, that these social investments were realized at the expense of income protection for the poor. This article assesses this potential trade-off with time-series cross-sectional models of the determinants of active labor market policies expenditures, childcare spending and the adequacy of minimum income protection (MIP), for 18 OECD countries between 1990 and 2009. It turns out that social investments are rather akin to traditional welfare state programs, and are explained by similar institutional, political and economic factors. More importantly, they do not develop at the expense of income protection. Social investment initiatives are consistent with the usual politics of the welfare state and, overall, they are not inimical to the poor.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.261
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.094
GPT teacher head0.413
Teacher spread0.319 · 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