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Record W7034629221

On Worlds of Welfare

2022· other· nl· W7034629221 on OpenAlexaboutno aff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2022
Typeother
Languagenl
FieldSocial Sciences
TopicHigher Education Teaching and Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101HyporeflexiaLiquationDiafiltrationDysgeusiaFusible alloyEmperipolesis
DOInot available

Abstract

fetched live from OpenAlex

Dit boek analyseert de instellingen en effecten van elf moderne welvaartsstaten (VS, VK, Canada, Australië, Duitsland, Frankrijk, België, Nederland, Zweden, Denemarken en Noorwegen). Aan de hand van kwantitatieve gegevens laten de auteurs eerst zien dat de institutionele verscheidenheid tussen deze landen kan worden teruggebracht tot drie hoofdtypen. Vervolgens onderzoeken ze de impact van deze drie 'werelden van welvaart': de effecten op inkomensherverdeling, ongelijkheid, armoede en sociale zekerheid. De studie maakt duidelijk dat instituties ertoe doen, maar ook dat de verdelingsresultaten van verzorgingsstaattypes niet zo eenvoudig zijn als je zou verwachten. Het biedt vooral een empirische basis voor het beleidsdebat over de sterke en zwakke punten van verzorgingsstaten.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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: Other · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.000

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 head0.028
GPT teacher head0.323
Teacher spread0.294 · 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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