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Record W4253574171 · doi:10.4324/9780429032202-10

Rout/e

2019· book-chapter· en· W4253574171 on OpenAlexaboutno aff
Chris Turnbull

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This chapter traces the development of rout/e, a poetry press (“footpress”) through which poems are installed along, or slightly off, trails in Eastern Ontario, Canada. This chapter considers the various features and processes, physical and conceptual, that affect the poems and the habitats in which they are encountered; through rout/e, poems are exposed to multiple influences and interactions that typically alter them. Whereas a bookshelf or library keeps poems pristine or collected in a literary, conceptual landscape, poems on and in the land, accessible by trails, emphasize the page, and the language on it, as a changeable landscape; the poems are read within a multiplicity of other markings and sounds, many of which are unrecognized by the human eye and ear. Trails serve many functions; for example, they can make for easier explorations of varied habitats and terrains by enabling movement over a variety of distances and through disparate geographies. The language of a poem, and the spatialization of a page, requires conceptual navigation and a reader’s willingness to access meaning in particular ways. In the rout/e project, each poem and its habitat are documented over several years (or until the poem disappears); contributions to rout/e are posted online, non-chronologically, with images and brief narratives that describe the poem in place (or displaced).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.881
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1710.016

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.

Opus teacher head0.016
GPT teacher head0.164
Teacher spread0.148 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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