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Record W2157797721 · doi:10.5267/j.msl.2014.1.025

The role of television in institutionalization of human resources principles in Iranian general policies of administrative system

2014· article· en· W2157797721 on OpenAlexvenueno aff
Javid Imani, Reza Najaf Beygi, Areyan Gholiopour, Ali Akbar Farhangi

Bibliographic record

VenueManagement Science Letters · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionalisationHuman resourcesSnowball samplingEconomic JusticePublic relationsNoticeDignitySociologyBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Iranian general policies of administrative system" is the mediator between the Islamic Republic of Iran vision in 2025 horizon and the practical field for establishing executive policies and laws, which is notified in 26 sections.This research aims to study the effects of television on institutionalization of six items of human resources principles in Iranian general policies of administrative system including human dignity, organizational justice, meritocracy, knowledge-basis, giving services in the deprived regions and honoring the retired.Research society consists of the management pundits familiar with media concepts.According to Grounded Theory and snowball sampling, 32 experts were interviewed and the institutionalization of human resources principles in Iranian general policies of administrative system model by television was extracted.The model discloses there has not been optimal utilization of television capacities for expressing the human resources principles in Iranian general policies of administrative system, but it is possible to use the capacity of television in planning and implementing these general policies.Considering the infrastructure and using appropriate strategies, television as the most influential mass media can be used in the axial issue, that is, the institutionalization of human resources principles in Iranian general policies of administrative system.It is crucial to notice the role of intervening factors in this area.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.242
Teacher spread0.224 · 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 designQualitative
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

Citations1
Published2014
Admission routes1
Has abstractyes

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