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Record W43814244

Under the maple tree

2009· dissertation· en· W43814244 on OpenAlexaboutno aff
Angela Marisol Roberts

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2009
Typedissertation
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsBrotherNarrativePortraitGenealogyArt historySet (abstract data type)Tree of life (biology)SociologyArtHistoryLiteratureComputer scienceAnthropology
DOInot available

Abstract

fetched live from OpenAlex

Set in a fictional Canadian suburb, this episodic novel centres on a group of characters of varying ages, social statuses, sexual orientations, and origins who are connected by relationships to each other and to their community. The lead protagonists of the novel are Violet Addams and Lucas Gibson, 20-something roommates, unwillingly sharing a townhouse. Lucas Gibson lives and works in the suburbs as a software engineer for a high technology firm. As the novel opens, Violet Addams, a recent university graduate, editor, and aspiring writer who finds herself at loose ends, moves to the suburbs to stay with her brother and his roommate, Lucas, and also to escape from the heartbreak of a failed relationship. Initially believing her circumstances to be temporary, Violet suddenly finds herself responsible for her brother's share of expenses when she discovers that he has fled his dissatisfying home life and complicated social life before she arrived. Violet and Lucas' time together begins. From this start, the narrative moves to stories about their immediate friends, relatives, and neighbours to create a portrait of the complex suburban experience. As time goes on, we see this group of characters evolve as we track their lives and loves.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.694
Threshold uncertainty score0.615

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.007
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0930.015

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 head0.036
GPT teacher head0.266
Teacher spread0.229 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2009
Admission routes1
Has abstractyes

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