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Record W4384701716 · doi:10.1016/j.ijlp.2023.101908

Mental health-related limitations and political leadership in Germany: A multidisciplinary analysis of legal, psychiatric, and ethical frameworks

2023· article· en· W4384701716 on OpenAlexaff
Alexander Smith, Stefan Theil, Stephen D. Hart, Michael Liebrenz

Bibliographic record

VenueInternational Journal of Law and Psychiatry · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHistory, Medicine, and Leadership
Canadian institutionsSimon Fraser University
FundersUniversity of OxfordWorld Health Organization
KeywordsMental healthPoliticsPolitical scienceContext (archaeology)DemocracyConstitutionalismPublic healthCorporate governanceLawPublic administrationPsychiatryMedicineNursing

Abstract

fetched live from OpenAlex

In recent years, political events have reignited contentious debates about psychiatry and democratic governance. This discourse has largely centred around the ethics and morality of public commentary, particularly in relation to the American Psychiatric Association's Goldwater Rule. Yet, few studies have examined the practical implications of health-related limitations due to mental illness in national leadership and the constitutional and legal provisions that surround these issues, including voluntary or involuntary proceedings. Accordingly, this theoretical paper analyses these topics in a German context using the position at the head of the executive: the chancellorship. Germany was selected as a case example as the biggest democracy in Europe with modern legal frameworks representative of the post-World War Two era in European constitutionalism, and for its economic and political influence within the European Union. Throughout this paper, we do not speculate on the mental health of any individual (past or present), but instead explore jurisdictional mechanisms around health-related limitations in German high office. Consequently, we outline relevant constitutional and legal scenarios, and how short- or long-term medical incapacity may determine requisite responses and contingent complexities. This underpins our discussion, where we consider legal ambiguities, functional capacity, and ethical concerns in psychiatric practice.

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 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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.037
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0080.023
Scholarly communication0.0090.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.386
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 source (direct Gemma or distilled Codex), 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

Citations7
Published2023
Admission routes1
Has abstractyes

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