Bibliographic record
Abstract
Books are artifacts of popular culture (Radway 1984, Thurston 1987, Illouz 2014). Paperback romances in particular have a social life beyond the single reader and the text (Jensen 1984, Newcomb 2002). “Vintage” category romances – commercial romance novels published twenty years old and older – can provide a fascinating data set for “community inquiry” (CoI), and a novel way to introduce students of writing to textual analysis. In its third iteration, my Ithaca College course Reading Popular Romance, is a writing-intensive first-year seminar taught using a Community of Inquiry (CoI) approach to instruction. CoI frames the classroom as a site of inquiry. My understanding of teaching writing is grounded in what Brian Street (1993) over twenty years ago named New Literacy Studies (NLS). NLS shares the Foucauldian notion of discourse as a powerful ideological rhetoric that frames people’s interpretations of everyday life. Through language we create, acknowledge, but most often presume mythologies and master narratives that in turn guide and make sense of our actions. The Category Romance Project requires students to use social science methods like discourse analysis and coding to explore romance as an artifact of popular culture. It asks students to think about romance critically, both as a master narrative and as an expression of the female imagination that is disdained like no other. This presentation will explain the course’s organization, pedagogical approach, and the Category Romance Project itself. It will provide examples of assignments and student work, and ask for feedback. WORKS CITED Illouz, E. (2014). Hard-core romance: Fifty Shades of Grey, best-sellers, and society. Chicago: University of Chicago Press. Jensen, M. A. (1984). Love’s sweet return: The Harlequin story. Toronto: Women’s Educational Press. Newcomb, L. H. (2002). Reading popular romance in early modern England. NY: Columbia University Press. Radway, J. A. (1984). Reading the romance: Women, patriarchy and popular literature. Chapel Hill: University of North Carolina Press. Street, B. V. (1993). "The new literacy studies, guest editorial". Journal of Research in Reading. 16 (2): 81–97. Thurston, C. (1987). The romance revolution: Erotic novels for women and the quest for a new sexual identity. Urbana: University of Illinois Press.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".