Blending and narrative viewpoint: Jonathan Raban’s travels through mental spaces
Why this work is in the frame
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Bibliographic record
Abstract
This article 1 applies the framework of conceptual integration (or blending) theory (as developed by Fauconnier and Turner) to the analysis of several travel narratives by Jonathan Raban. The primary goal of the article is to show how the analysis of blending strategies used in the text may help in the recognition of the specific features of a writer’s narrative style. An extensive discussion of a variety of blends appearing in Raban’s texts also serves as a background to the discussion of the relation between choices of blending strategies and the allocation of narrative viewpoint. It is argued that the concept of narrative viewpoint crucially relies on the structure of blending networks. Finally, it is shown how interpretation of viewpoint phenomena in the narrative builds on the mechanism termed viewpoint compression.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it