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Record W4409476428 · doi:10.53103/cjlls.v4i5.176

Novel Negeri 5 Menara by Ahmad Fuadi: What Education Is Worth It?

2024· article· en· W4409476428 on OpenAlexvenueno aff

Bibliographic record

VenueCanadian Journal of Language and Literature Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Character Development
Canadian institutionsnot available
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

This research aims to explanate and elaborate the values of education in the novel Negeri 5 Menara by Ahmad Fuadi.The primary data source of this research is the novel Negeri 5 Menara.The results of the research show that the novel Negeri 5 Menara represents important educational values for readers.The educational values in the novel are a valuable source of knowledge that can guide humans to achieve stability in society.Perseverance and independence are important pillars that show how the main character continues to struggle despite facing various obstacles, emphasizing the importance of resilience and independence.Social values such as empathy, effective communication, cooperation and leadership highlight the importance of interpersonal skills in forming a harmonious and collaborative hubunagn.The culture and aesthetics in this novel invite readers to appreciate and preserve cultural heritage and find beauty in daily life.Through a strong narrative and beautiful language, Fuadi succeeded in conveying moral messages that are relevant to the context of contemporary character education.The implications of this analysis show that the Land of 5 Towers can be an effective tool in character education, providing students with real and inspiring examples of how noble values are applied in daily life.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.330
Teacher spread0.314 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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