The issues of travel in the two works Chaos of freedom and let me speak! of the writer HMDANE Halima
Bibliographic record
Abstract
The concept of travel has long been associated with the human experience and is considered an essential aspect of individual presence, existence, and development. It is viewed as a factor that reveals an individual's actions within a spatial and temporal framework and has significant universal significance across all social classes. While the domains and motives of travel may differ among individuals, the theme of travel holds a particular importance in literature. In this study, we focus on the issue of travel in Halima Hamdane's two works, Let me speak! and Chaos of freedom. We adopt a sociological approach to analyze the psychological state of the characters, study their social belonging, and its impact on their behavior. Our objective aims to examine the treatment of this theme in these two literary works that are part of the oral literature tradition. Additionally, our focus is on the profile of two specific characters in relation to the author's narrative and argumentative structure. Through our analysis, we seek to understand the significance of the theme of travel in these works and its impact on character development. Our research aims to provide insight into how travel is utilized by the author to advance storyline and enhance character mobility. Moreover, it seeks to explore how travel impacts character behavior and action, as well as the relationship between social belonging and travel. By adopting a sociological approach to analyze the psychological state of the characters, we can gain a deeper understanding of how travel serves as a means of self-discovery and personal development. Furthermore, our analysis can shed light on the broader cultural and societal implications of travel in literature. Ultimately, our study contributes to a deeper understanding of the role of travel in literature and its impact on individual and collective identity.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".