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Record W2564123910 · doi:10.5539/jpl.v10n1p84

Realization of Human Security in Light of Good Governance

2016· article· en· W2564123910 on OpenAlexvenueno aff
Maedeh Samadi, Seyyed Bagher Mirabbassi

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSuretyHuman securityHuman rightsCritical security studiesCorporate governanceEnforcementContext (archaeology)Face (sociological concept)Security through obscurityNational securitySecurity studiesPolitical scienceLaw and economicsPublic administrationBusinessLawNetwork security policySociologyCloud computing securitySecurity information and event managementSocial scienceFinance

Abstract

fetched live from OpenAlex

Support of human rights and the appearance of “human security” issue in the new system of international law as a newfangled concept, has led to a change in traditional outlook towards security. In the present paper beside taking into consideration the concept of security in Realist and Liberal Perspectives, the developmental performance of the state regarding enforcement of rules (as the first serious addressee of providing and guaranteeing human rights in international rights system) from national security with a focus on human security in the context of good governance was considered as well. The primary objective of the study was to understand the effect of good governance on human security realization. In such a way that states would be able to increase the coefficient of human security provision and guaranty by changing the method of governance in their territory. Also, reforming the governance structure besides taking steps to strengthen individuals in the face of human insecurity is also a coherent approach to providing a helpful background for civil society.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.012
Scholarly communication0.0050.003
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.289
Teacher spread0.279 · 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 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
Published2016
Admission routes1
Has abstractyes

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