Information activities as serious leisure within the fanfiction community
Bibliographic record
Abstract
Purpose Fanfiction communities are actively engaged in creating cultural products. These large online communities have created and developed conventions that guide their solutions to gathering and presenting their work. The purpose of this paper is to investigate those conventions looking for evidence of information-related pursuits as serious leisure (SL) (Stebbins, 2007). Design/methodology/approach A diverse collection of fanfiction publishing platforms, blogs, and associated websites were subject to a qualitative inductive analysis (Lincoln and Guba, 1985). Platforms included both generalist sites like Archive of Our Own and more focused sites such as Teen Wolf Fic Finder. Findings Findings show significant information-related activities around collecting, wayfinding, and organizing. Collecting centers on platform policies focused on scope. Wayfinding relates to peer review as well as various reference-like work including reader’s advisory, reference questioning, and the creation of pathfinders. Organizing looks to the unique organizational schema created and used by the fanfiction communities. Research limitations/implications The authors explore implications of these activities in reference to the fanfiction community and the library and information science (LIS) discipline. The fanfiction community is shifting out of an ephemeral existence and into one of a more permanent digital heritage. Fanfiction is an SL pursuit that also has much to offer for consideration to the LIS discipline. Practical implications With respect to the wayfinding and organizing conventions of fanfiction communities, these activities provide librarianship with the opportunity to consider traditional activities in new ways. Originality/value Fanfiction is a little studied phenomenon in SL and in LIS. This research provides connections to both areas.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".