MOTIVE AND CHARACTER EDUCATIONAL VALUES IN NOVEL THE INVENTION OF HUGO CABRET BY BRIAN SELZNICK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>This is a descriptive qualitative research that uses a psychological approach. The data source of this research is the novel The Invention of Hugo Cabret by Brian Selznick, publisher of Scholastic Press, New York (original version) in 2007, Mizan Fantasi (Indonesian version) in 2012. The research data are in the form of words, phrases and sentences that related with the main character's motives and the character education values in the novel. Data obtained by reading and note taking techniques. This objective of this study to analyze the existence of the main character's action motives and the value of character education in the novel The Invention of Hugo Cabret by Brian Selznick. The results of the analysis obtained the following conclusions: 1. Hugo's motives as the main character there are 20 quotes, namely as follows: a) motives for physical needs there are 3 quotations, b) motives for security and safety needs are 4 quotations, c) motives for trust and compassion consist from 5 quotations, d) the motive for self-esteem needs there are 3 quotations, e). The motives for self-actualization needs are 6 quotations. The prominent action motive is the motive for self-actualization needs. 2. The value of character education contained in Brian's novel The Invention of Hugo Cabret, consisting of; a) religious 2 quotes, b) honest 4 quotes, c) discipline 3 quotes, d) hard work 7 quotes, e) creative 2 quotes, f) independent 1 quote, g) curiosity 4 quotes, h) appreciate achievement 2 quotes, i) friends 3 quotes, j) peace love 1 quote, k) likes to read 2 quotes, l) social care 4 quotes, m) responsibility 2 quotes.</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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it