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Protocol: Realist synthesis of the impact of unemployment insurance policies on poverty and health

2014· article· en· W2011328276 on OpenAlexaff
Ágnes Molnár, Patricia O’Campo, Edwin Ng, Christiane Mitchell, Carles Muntañer, Émilie Renahy, Alexander St. John, Ketan Shankardass

Bibliographic record

VenueEvaluation and Program Planning · 2014
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsWilfrid Laurier UniversityUniversity of Toronto
Fundersnot available
KeywordsUnemploymentPovertyEconomicsContext (archaeology)Public economicsActuarial scienceEconomic growth

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.046
metaresearch head score (Gemma)0.168
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.233
Threshold uncertainty score0.778

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.168
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0040.005
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0030.004
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.2330.025

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 head0.183
GPT teacher head0.546
Teacher spread0.363 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations39
Published2014
Admission routes1
Has abstractno

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