French and Venezuelan People’s Conceptualization of Human Rights: Indivisibility and Universality Issues
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".