“It was always what was under the poetry that mattered”: Reading the Paratext in Once in Blockadia by Stephen Collis
Bibliographic record
Abstract
Once in Blockadia by Stephen Collis is poetry of direct action, a book of revolutionary record where the speaker is a participant in the protest. Collis radically challenges traditional uses of form, breaking the bounds of the poem and asking the reader to engage more deeply with his text. The organizational metaphor of the barricade connects with the poetry’s social and political aspirations but also showcases a blockade of normative reading, one where the text is a contained entity. Guided by literary theorist Gerard Genette, structural analysis of Once in Blockadia allows a comprehensive picture of its intertextuality. An active reading—from covers and epigraphs to interviews, legal transcripts, and news reports, in what I call a critical literary praxis of ‘reading the notes’—provides unique understandings of poetry that highlights the complexities of interacting with a text that is forever unfinished for both the writer and the reader. The active nature of this paratextual writing and reading challenges the dominance of the author or publisher over a text, opening the closed poem to a democracy of voice, content, and meaning. For Once in Blockadia, every context is a paratext and every paratext becomes, granularly, part of the text itself.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.030 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".