Fandom as Magical Practice: Great Big Sea, Stockwell Day, and Spoiled Identity
Bibliographic record
Abstract
and graduate courses in folklore and popular culture that explored small group ex-pressive uses of mass-mediated materials. Of the many paper topics fitting this theme, ethnographies of fandom predominated. Thus I discovered through my stu-dents ’ work that several basements in St. John’s housed Star Trek main bridges be-decked with life-size cutouts of Captain Picard and Data, major Star Trek characters; that home shrines and displays lovingly devoted to Elvis were common-place; and that carloads of young Newfoundland women made pilgrimages to the United States to see the Indigo Girls perform live. In general, the conclusions of my students stressed the positive activities of audiences, not the pathology of fanatics (see Jenson 1992) who Theodor Adorno would have viewed as the dupes of a monolithic popular culture industry (1991). In 1987 several of my graduate stu-dents ’ ethnographies of fans were published in a special section on “fandom ” in the folklore graduate student journal, Culture & Tradition (Volume 11). These exami-nations highlighted fan creativity, their collection and display of artifacts, and their social networking. Since then, fandom studies have burgeoned. Most notably, folklorist Camille Bacon-Smith’s extensive study, Enterprising Women: Television Fandom and the Creation of Popular Myth (1992), developed a positive view of fandom fur-ther by detailing how groups of women have used the frame of Star Trek to cre-atively communicate with one another about mutual concerns and life values. Relatedly, cultural studies scholars have drawn on Antonio Gramsci’s theory of hegemony to interpret fans as members of more active audiences than average consumers. These analyses have underscored the subversive nature of fan groups
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".