The Convergence of Mental Spaces and the Personification of Time, Tenacity and Patience in the Novel by Alexander Zalan “The Last Row”
Bibliographic record
Abstract
The fact that society exists, evolves and subsequently modifies the means of interaction, cannot be denied.It is solely possible due to people's abilities to enact a mutual link on myriad levels, i.e., social, cultural and cognitive.Nevertheless, there are certain innately entrenched constituents that shape our perception, interpretation and assessment.The dominant concept of my PhD thesis (Cognitive Discourse: Cultural Cognitive Models in the Use of Language) is mental spaces and their potential aptitudes, i.e., analogy mapping, identity connection, mental space framing, the convergence of mental spaces and the moulding or alteration of initial perception of various notions.It must also be noted that although language varies in its surface peculiarities in numerous cultures, this variety is underpinned by universal psychological mechanisms that generate further cultural cognition (Chomsky, 1975; Pinker, 1994).The theory considered, it is probable to draw certain parallels within the framework of the novel "The Last Row" (2021) by attributing mental spaces to a pervading realm of a fantasy novel, delineating core qualities of the main characters and depicting their peculiar features by converging the author's subjectivity, objective implicatures and virtual implications, thus displaying the applicability of mental spaces not only within the framework of cognitive linguistics or psycholinguistics, but also bringing it further to other academic spheres.The core impetus of this article underlies the scope of analysis that can be attributed even to the most inconspicuous elements of any work, fracturing implications and implicatures and delineating the difference between instant assessments and hypothesis, and ultimate results, implying wholly accumulated elements.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| 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".