Bibliographic record
Abstract
Palmer's distinction between intramental, or personal, and intermental, or shared thought is undeniably valid from both an intuitive and an empirical perspective. It is hard even imagine a novel devoid of some conflict between individuals and collective norms, values, or biases of their social context, and indeed all contains some variation of this indispensable ingredient. Given narratology's lack of attention representation of intermental thoughts, it is be hoped that Palmer's directive for a systematic investigation of this issue will be heeded. His analysis of Middlemarch passages, which consists of identification of textual features used represent social minds, makes it clear that narratological approach is most appropriate for specific research project he clearly identifies in second part of his essay, namely development of a of social As a means achieve that goal, he rightly argues, it is necessary amass textual data regarding strategies and features used represent social minds in fiction. Once enough evidence is collectcd, it might be possible detect in way social minds are represented across time, and this in turn would advance our understanding of evolution of novel. The articulation of this particular goal and role of narratology in accomplishing it are most persuasively argued aspects of Palmer's essay. That narratology can be put at service of history is uncontroversial. Less clear, however, is relationship between this historical goal and very schematic cognitive framework he defends in first part of his essay (which constitutes approximately two-thirds of whole). Although this paper may not have been establish a coherent conceptual framework, bur rather make a case for usefulness of cognitive theories for narratological purposes, there does seem be a disconnect between cognitive and narratological in his argument. Throughout his long discussion of cognitive theories, Palmer drops many names of both cognitive scientists and literary scholars who make use of their research. Periodically, he very briefly alludes a few general insights and ideas within umbrella field of what he calls soft cognitive sciences. What one gleans from this long discussion is that main advantage of cognitive theories and approaches is their ability shed light on reading processes of real readers. He laments that narrative theory has taken insufficient account of practice of actual states that the constructions of minds of fictional characters by narrators and readers are central our understanding of how novels work ..., and declares that his aim is to show how readers make sense of fiction, explain processes that we all engage in ... In keeping with this goal, he offers several explanations about how readers construct elements of story world; for example, how they process plot, how they how they bring real world knowledge bear on text, and how they are able follow workings of characters' Given explicit narratological-historical goal stated towards end of his essay, first question that arises is how cognitive goal of understanding readers' mental processes is related narratological goal of identifying textual features used depict social minds. These appear be two very different objectives, equally laudable and necessary, but not obviously compatible. In other words, main problem that Palmer has not solved is precisely that of how reconcile narratological goal of analyzing textual features with cognitive interest in reader constructions. This reconciliation between narratological and cognitive is possible, but not necessarily in a way that would serve purpose of identifying historical patterns in representation of social minds. …
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.027 | 0.046 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".