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French and Venezuelan People’s Conceptualization of Human Rights: Indivisibility and Universality Issues

2018· article· en· W2900123666 on OpenAlexaff
Ana Gabriela Guédez, Étienne Mullet

Bibliographic record

VenueUniversitas Psychologica · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsConceptualizationUniversality (dynamical systems)Civil libertiesHuman rightsPoliticsSociologyInequalitySocial psychologyPolitical scienceLawPsychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

The present study aimed to examine French unpaid participants’ (N = 50) perceptions about Human Rights (HR). The material was a series of scenarios depicting a socio-political situation of a fictitious state and a response scale. Four critical items of information were provided: (a) the degree in which the State offers social protection to the citizens (not at all, intermediate or complete);(b) the level of respect for Civil Liberties in the country (no respect, intermediate, full respect);(c) the level of Equality between citizens (inequality of rights vs. equality of right);and (d) the level of Respect for the private life of the citizens (no respect for private life vs. full respect for private life). The 36 stories were obtained by the orthogonal crossing of the four factors: 3 x 3 x 2 x 2 = 36. Results from the French sample were compared with previous results from a Venezuelan sample (Guédez & Mullet, 2014). Results showed no difference in the importance given to Social Protection between French and Venezuelan participants. Also, the crucial four-way interaction was significant at a very stringent level, and the five-way interaction involving Country was not. Thus, it can be safely considered that the way HR are conceptualized is correctly expressed by the equation: Judged Respect for HR = Privacy x Civil Liberties x Equality x Social Protection.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.341
Teacher spread0.307 · 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 designObservational
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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