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Record W3159013211 · doi:10.24908/iqurcp.8328

The e ‐ Narrated Self

2016· article· en· W3159013211 on OpenAlexvenueno aff
Celine Song

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeStorytellingPlot (graphics)Point (geometry)HappeningAestheticsNarrative structureSociologyLiteratureHistoryMedia studiesArtPerformance artArt history

Abstract

fetched live from OpenAlex

A common question asked about the web 2.0 by the offline population is: "What do people do there?" The paper addresses this question with respect to Paul Ricoeur's narrative theory of the self. According to his essay Life in Quest of Narrative, a person drifts through time experiencing events happening to them, but none of it is actually lived when it is not "recounted" or "storied". In this light, "storytelling may be said to humanise time by transforming it from an impersonal passing of fragmented moments into a patter, a plot ,a mythos". Blogs and sites like Facebook represent the most recent development in the human attempt to weave this "mythos". A profile page and a tweet are first and foremost stories that appear to its critics "truncated or parodied" by design "to the point of being called micro-narratives or post-narratives", and to it s advocates"multi-plotted, multi-vocal and multi-media". The paper introduces notions of e-Self and e-Narrative, examines their dangers and benefits, and concludes that "the advent of cyber-culture should be seen not as a threat to storytelling but as a catalyst for new possibilities of interactive, non-linear narration".

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.190
GPT teacher head0.464
Teacher spread0.274 · 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.

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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