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Record W4230468601 · doi:10.24124/2016/bpgub1135

Spaces for interpretation: story telling in autobiographical fiction and visual art

2016· dissertation· en· W4230468601 on OpenAlexaff
Andrea Sophia Fredeen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsEmily Carr University of Art and DesignUniversity of SaskatchewanUniversity of Northern British Columbia
Fundersnot available
KeywordsNarrativeStorytellingBiographyInterpretation (philosophy)Reflexive pronounArtAutobiographical memorySubject (documents)LiteraturePerspective (graphical)AestheticsVisual artsPsychologyLinguisticsPhilosophyComputer scienceRecallCognitive psychology

Abstract

fetched live from OpenAlex

There is an innate human drive to share stories of self. In this thesis, I explore the idea of creating autobiographical fiction through written and visual art forms. A key challenge is how to tell a story based on a life event without disrespecting actual people or distorting recollected events. I begin by considering the concept of autobiography, the nature of memory, its close relationship to fiction, and the relationship between these, identity, and storytelling. I discuss the possibility of a more complete understanding of the story being told when an author also employs an alternative narrative form. Using myself as a subject, I engage in a form of autoethnography to create fictional short stories that have an autobiographical thread. Each story is accompanied by a work of visual art as further narration of the same story. I conclude by suggesting that using the two narrative forms of written and visual art provides an individual with the opportunity for an alternative perspective, which allows for a more clear understanding of self and position in the world. --Leaf ii.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.588

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)0.0000.000

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 head0.028
GPT teacher head0.409
Teacher spread0.381 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

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