Space-time and the production of meanings in Nuno Bragança's Directa
Bibliographic record
Abstract
Various disciplines have studied the Space and Time categories over time, both separately and together. For humans, according to Tuan, “The experience of space and time is largely subconscious” (2014, p. 118). As in human experience, these two categories are inseparable in narrative genre because “‘story time’ emerges from the interplay of space, events, characters, and plot structure” ( Scheffel, 2014 ). The inseparability of Space and Time is also present and visible in a city, as shown by several authors. Concerning these two categories, in Nuno Bragança’s novel Directa , the author explores simultaneously the potential offered by the city of Lisbon and the narrative genre. In this chapter, we intend to show how the author treats space and time in the novel, especially, how he uses the practice of the city space as an intentional way to establish and treat various times and build essential messages of the work, especially through hero maps and routes, and reflections.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.025 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".