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Record W3122318661

Compensation Schemes for Damage Caused by Healthcare and Alternatives to Court Proceedings in the Netherlands: The Netherlands National Report to the 20th General Congress of the International Academy of Comparative Law, Fukuoka, Japan, 22-28 July 2018

2018· article· en· W3122318661 on OpenAlexaff
B.S. Laarman, A.J. Akkermans

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsCompensation (psychology)ComplaintLegislationHealth careLiabilityPolitical scienceLawTortBusinessLaw and economicsSociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

In the Netherlands, concerns about the negative experiences of patients with legal procedures following adverse medical events have led to potentially profound changes in the field of procedural complaint- and compensation law. This report offers insight into the Dutch legal framework of compensation for damage caused by healthcare. We start by presenting the traditional framework in part A: The Dutch landscape of medical liability. Having laid the groundwork, we try to explain the innovations that have recently been introduced, in part B: Efforts for reform. We elaborate on the problems patients experience when they claim for compensation, the impact legal procedures can have on both patients and healthcare professionals, the recent changes in legislation trying to address these problems, and how these changes force both healthcare and legal professionals to adapt to a new reality.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.445
Teacher spread0.341 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2018
Admission routes1
Has abstractyes

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