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Record W2487717891 · doi:10.5539/jpl.v9n6p177

An Analysis of the Role of Human Dignity in the Iranian Citizens Rights Charter

2016· article· en· W2487717891 on OpenAlexvenueno aff
Fatemeh Piraman, Seyed Mohammad Sadegh Ahmadi, Masoud Raei

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsnot available
Fundersnot available
KeywordsDignityCharterHuman rightsCitizenshipPolitical scienceLawFundamental rightsContext (archaeology)Social rightsLaw and economicsSociologyPolitics

Abstract

fetched live from OpenAlex

<p>In today's societies, in which the variety of social communications are increasingly expanded, citizenship rights in relation to all citizens equally and without discrimination depends on a comprehensive charter. This charter should specifically predict citizenship rights. The citizenship Bill of Rights will only be successful in achieving its goals in case it is principally based on the human dignity. The Iranian legal system in 1392 experienced the development of the "Citizens Rights Charter". This charter, with its fundamental drawbacks, will not have a desirable impact on the Iranian legal system.<br />Apparently, human dignity enjoys a proper position in the introduction and the general rules of the Iranian Citizens Rights Charter. However, the charter's understanding of the concept of citizen and government has compromised this condition. On the one hand, considering the citizen as anonymous with the national, and granting citizenship right to the state on the other hand have compromised the the position of human dignity in the charter.<br />With respect to the instances of civil rights, human dignity does not enjoy an appropriate position too. The lack of distinction between instances of human rights and mere citizenship rights, non-implementation of instances in a comprehensive framework and the over-emphasis on counting the instances by the law, has undermined human dignity in the citizen rights context.</p>

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 score0.446
Threshold uncertainty score0.077

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 studies0.0000.000
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 head0.024
GPT teacher head0.298
Teacher spread0.274 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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