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PERKEMBANGAN KEJIWAAN MUSA DALAM NOVEL MADIELIEF KARYA KIRANADA: KAJIAN TEORI PSIKODINAMIKA SIGMUND FREUD

2023· article· en· W4386714265 on OpenAlexaboutno aff
Hanikmah Rahmadani, Tengsoe Tjahjono

Bibliographic record

VenueTRANSFORMATIKA JURNAL BAHASA SASTRA DAN PENGAJARANNYA · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)PsychologyNeuroticismReading (process)PsychodynamicsStatement (logic)PsychoanalysisPersonalityEpistemologyLinguisticsPhilosophyMathematics

Abstract

fetched live from OpenAlex

<p>Novels are never separated from psychological values because the problems told in novels are always related to the psychology of the characters created by the author. This psychological aspect is usually displayed through the character traits and behavior of the characters that are a problem as experienced by humans in real life. Like the novel Madielief by Kiranada which tells the psychological problems of the characters in it. Therefore, this research is examined using psychodynamic theory which aims to describe the psychological development of characters according to Sigmund Freud. This type of research is qualitative research with a literary psychology approach. The data were obtained from the novel Madielief by Kiranada. Research data are in the form of words, phrases, and sentences in paragraphs related to the problem statement. Data collection techniques using reading and note techniques. The results of this study indicate 1) Musa’s personality background in Kiranada’s Madielief novel, 2) Musa’s neurotic form of anxiety in Kiranada’s Madielief novel, 3) The psychological development of Musa in the Canadian Madielief novel</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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0030.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.278
Teacher spread0.247 · 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.

Study designOther design
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
Published2023
Admission routes1
Has abstractyes

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