Bibliographic record
Abstract
Carolyn Miller’s (1984) “Genre as Social Action,” the primary topic—or target—of Anne Freadman’s brilliant and thought-provoking article, holds a special place in genre research. If I pick up an unknown piece of research on genre, the first thing I do is look for Miller’s article in the bibliography. If it is not there, the text in my hand will probably be of little of value to my work for lack of orientation. Moreover, as Freadman (2012) notes, convention in genre research suggests that when you mention the article, it is in good form to add a positive qualifier. It will often be framed as having “formative influence” (MacNeil, 2012), as a “landmark essay” (Feinberg, 2015), or as “seminal” (Andersen, 2008; Devitt, 2009a; Motta-Roth & Herbele, 2015; Møller, 2018; Paré, 2014; Tachino, 2012), “groundbreaking” (Bawarshi, 2000; Smart, 2003; Winsor, 2000), or “oft-cited” (Devitt, 2009b). More than just paying lip service to the greats in the field, adding this qualifier demonstrates that the author knows her way around Rhetorical Genre Studies and is mindful of Miller’s central place within it. This status as a classic text is in itself an example of the bidirectionality of uptake that holds a central place in Freadman’s work. “Genre as Social Action” could not be canonical when it was first published. A canon had to form, and the article’s central place within it had to be recognized by later researchers, before Miller’s text could be taken as oft-cited, seminal, or groundbreaking.
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 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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".