Narratives of Fact and Fiction: Examining Studies of Information Experience and the Interpretation of Data.
Bibliographic record
Abstract
This paper reports on an ongoing pilot study of creative engagement with fictional worlds in order to explore potential contributions of narrative methods and data to the investigation of information behaviour and experience in LIS. A narrative framework can be used to examine the individual, social, and material aspects of information experiences situated in time and space. Such a framework has the potential to contribute detailed understandings of the nature of the experience of information and fiction, and of information experience more generally, to the body of literature on information experience in LIS.Cet article rend compte d'une étude pilote en cours sur l'engagement créatif avec des mondes fictifs afin d'explorer les contributions potentielles des méthodes narratives et des données à l'investigation du comportement et de l'expérience informationnelles dans les sciences de l’information et la bibliothéconomie (SIB). Un cadre narratif peut être utilisé pour examiner les aspects individuels, sociaux et matériels des expériences informationnelles situées dans le temps et l'espace. Ce cadre peut contribuer à la compréhension détaillée de la nature de l'expérience informationnelle et de la fiction, et de l'expérience informationnelle en général, ainsi qu’à l'ensemble de la littérature sur l'expérience de l'information dans les SIB.
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 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 | 0.001 | 0.009 |
| 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 | 0.004 |
| Scholarly communication | 0.001 | 0.027 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".