A theoretical framework for narrative explanation in science
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper deals with a number of conceptual and theoretical issues that underlie the proposal to employ narrative explanations in science education: What is narrative? What is explanation? and What is narrative explanation? In answering these questions, we develop a framework of narrative elements and characteristics of narrative explanations. Two possible examples of narrative explanation are presented and examined in light of the framework. This examination brings to light various conceptual and empirical questions related to the examples and to the larger issue of the use of examples like them in science instruction. The value of the framework lies partly in its power to point to such questions. The questions can guide a program of theoretical and empirical research into the psychological reality of the narrative form of explanation, the existence of narrative explanations in science, the use of narrative explanations in science teaching, and the nature and extent of the narrative effect upon which proposals for the use of narrative often are justified. © 2005 Wiley Periodicals, Inc. Sci Ed, 89:535–563, 2005
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.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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