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Record W2107092486 · doi:10.1111/1467-9647.00134

Reading Images in the Religious Studies Classroom

2002· article· en· W2107092486 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTeaching Theology & Religion · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicStudy and Philosophy of Religion
Canadian institutionsRoyal College of Physicians and Surgeons of CanadaMount Royal University
Fundersnot available
KeywordsReading (process)Field (mathematics)Interpretation (philosophy)Task (project management)TRIPS architectureComputer scienceMathematics educationKey (lock)Teaching methodEpistemologyPsychologyLinguisticsPhilosophyMathematics

Abstract

fetched live from OpenAlex

This note presents a method for teaching students to analyze and interpret images in the religious studies classroom. The technique uses two separate exercises: first analyzing images as works of art and then as conveyors of discipline‐specific information. Drawing on the work of Edmund Feldman, our technique grounds interpretation in a methodical description of the basic components and characteristics of images. By helping students to conceptualize the formal qualities of an image as a first exercise, this technique allows them to more confidently address the challenging task of relating aspects of a given image with key concepts of religious studies. This simple first step toward interpreting religious images can help students profit more from texts, videos, lectures, field trips, and further studies in the field.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.591
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.280
Teacher spread0.230 · 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