MétaCan
Menu
Back to cohort
Record W7096552600

Print PDF Version Reading New Worlds

2016· article· en· W7096552600 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMacabreReading (process)NothingAgency (philosophy)WonderFalling (accident)NewspaperPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

My earliest understandings of the agency of story exist within my memories of the third grade. While, in later years, much has helped refine those childhood insights, nothing has served to nullify them. Both my parents were readers; interestingly, they seldom read to us. My mother, raised in various log cabins in the north of Alberta, was a human tome of macabre stories involving young girls falling off horses and dying of concussion, of schoolhouses catching fire, of bodies stored in granaries waiting until spring to be buried, of the roving uncle who dropped in annually for his bath, of long-haired hermits and keening widows, of stillborn babies swathed in cotton batting and buried in roughhewn boxes. The stories of my father's family were constructed from the shadowed allusions, made by aging aunts and uncles, to the atrocities of Stalinist Russia. These fragments, told with unfocused eyes and flushed faces, were more fearful for their imagined horror than for details truly known. Like my mother's tales, the theories they inspired threaded through my days, organizing my interpretations of the world as an unpredictable, adventurous place, with exotic events and hidden dangers waiting to be experienced and conquered, or avoided. Such was my association with story until I went to school. Grades one and two were spent in plaid phonics workbooks, exploring the "wonders " of /a / and /b/, and in

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 score0.743
Threshold uncertainty score0.994

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)0.1330.007

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 head0.014
GPT teacher head0.214
Teacher spread0.200 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicThemes in Literature AnalysisFrench-language works237,207