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Record W4399763751 · doi:10.3138/ijmsch-2023-2301

Autonomy and Care: Bioethical Principles for Understanding Masculinities in Unemployed Men

2024· article· en· W4399763751 on OpenAlexvenueno aff
Giovane Mendieta Izquierdo, Juan María Cuevas Silva

Bibliographic record

VenueInternational Journal of Men s Social and Community Health · 2024
Typearticle
Languageen
FieldMedicine
TopicEthics and bioethics in healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsBioethicsAutonomyThematic analysisNarrativePerspective (graphical)SociologyPhenomenonQualitative researchSocial sciencePolitical scienceEpistemology

Abstract

fetched live from OpenAlex

Introduction: This study proposes an interdiscursive perspective between bioethics and the social and human sciences to understand the phenomenon of unemployment from the male perspective. The objective of the study is to analyse the bioethical principles of autonomy and care for the understanding of masculinity in unemployed men. Method: Qualitative case study from Yin's perspective with a hermeneutic approach, through in-depth interviews with a narrative biographical emphasis. Seven heterosexual men from Bogota, without employment and with family, were recruited through a combined purposive and convenience sampling process. Thematic analysis of the data was carried out after open coding of the narratives, which allowed the construction of families and emerging categories. Results: The main findings revolve around the principles of autonomy and care as macro categories of the social and human sciences and bioethics from a comprehensive perspective. Discussion: The analysis of the bioethical principles of autonomy and care provides key elements to build interdiscursive and interdisciplinary bridges between bioethics and the social and human sciences. It does this by addressing the social phenomenon of unemployment in men and its implications in the rupture of mental and contextual models of men that contribute to the understanding of masculinities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.370
GPT teacher head0.483
Teacher spread0.113 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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