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Record W7062390728

Two Roads to Middle-earth Converge: Observing Text-based and Film-based Mental Images from TheOneRing.net Online Fan Community

2011· dissertation· en· W7062390728 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2011
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMental imageComprehensionAdaptation (eye)Reading (process)Mental modelVisualizationCognitionOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

Mental imagery as a form of human cognition is still not well understood, particularly in the area of spatiality. This thesis attempts to find the relationship between the mental images of places created while reading a story (ekphrastic) and the mental images created while viewing a cinematic adaptation of that story. Using Bakhtin’s idea of chronotope, and Panofsky’s theory of iconography, associations can be made between places in text and film that inform the themes that readers/spectators identify and evaluate. Netlytic, an online text analysis tool, permits the analysis of online message board fan opinions of J.R.R. Tolkien’s and Peter Jackson’s The Lord of the Rings according to themes of visualization and of place. Analysis of findings suggests that mental images created from the text and from the filmic adaptation are both passively and actively integrated in order to increase comprehension of spatial elements in Tolkien’s epic.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.165
Teacher spread0.158 · 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