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Secrets in the Open: An Exercise in Interpretive Writing

2016· article· en· W4400610514 on OpenAlexaffvenue
Galicia Blackman

Bibliographic record

VenueJournal of Applied Hermeneutics · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInnocenceCharacter (mathematics)AestheticsPsychologySecrecyPsychoanalysisArtComputer science

Abstract

fetched live from OpenAlex

In this paper I present an exemplar of interpretive writing based on my engagement with the movie, My Life as a Dog. The film is a series of vignettes about Ingemar, a young boy, who is processing the events which arise from the difficulties wrought by his mother’s illness. This is not the typical coming of age film where the child becomes an adult through the initiation into life’s painful circumstances. The film ends with the character still in his boyhood. Nevertheless, the intermittent voice-over conveys the impression that Ingemar is narrating in retrospect, in a build up to his emergence from a state of innocence to awareness, and acceptance of pain and loss. I attended to the principles of hermeneutic practice outlined by several scholars to frame my understanding of what it means to enter the hermeneutic circle to explore the topic which addressed me: Secrecy.

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)0.076
metaresearch head score (Gemma)0.071
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.076
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0210.161
Scholarly communication0.0280.035
Open science0.0040.019
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0030.001

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 head0.059
GPT teacher head0.301
Teacher spread0.242 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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