Merely Telling Stories? Narrative and Knowledge in the Human Sciences
Bibliographic record
Abstract
This essay is part of a long-term cross-disciplinary research project,entitled “Narrative between the Disciplines,” which looks at the way narrative is used within and between different disciplinary formations. Its goal is to say something about narrative itself as a form of redescription, a mode of knowledge, and how the claims made for it by the various disciplines say something about their own opera-tions, limitations,and presuppositions. By examining the diverse ways narrative is inflected in different institutional settings, we might also discover something about our concern for narrative now and our notions of disciplinarity and the compartmentalization of knowledge. Elsewhere, I have already sketched out some of the basic questions regarding the recent explosion of interest in narrative and in theorizing about narrative across the disciplines: Why narrative? And why narrative now? Why have we decided to trust the tale? This essay develops some of the questions that my earlier work left open; more specifically, it deals with the inherent “bivalency” of narrative—its dependency on the temporalities both of the telling and of the told—and charts the history of the recent “narrativist turn.” It attempts to present a genealogy of the different ways in which disciplines in the human sciences have formulated and employed narrative and narrative theory,particularly in those fields that make truth claims: history or political science, for example. Why have political scientists now decided to“trust the tale”? Is their sense of narrative the same as say,literary theorists'? And what might these things say about their own discipline and the relations between it and other disciplines in the human sciences?
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.078 |
| Scholarly communication | 0.015 | 0.028 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".