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Record W3041243564 · doi:10.3167/jys.2020.210105

“Welcome to Divinity College”

2020· article· en· W3041243564 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

VenueJourneys · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Tourism and Spaces
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDivinityPilgrimageIgnoranceIndoctrinationState (computer science)NationalismSociologyChivalryPower (physics)HistoryMedia studiesPolitical scienceLawIdeologyAncient history

Abstract

fetched live from OpenAlex

“Welcome to Divinity College,” reads a welcome sign to the state-sponsored fieldtrips of the Iran-Iraq War (1980–1988) battlefields in Iran. Rahian-e Noor battlefield tours follow the model of Shia pilgrimage and commemorative rituals, while also tapping into nationalist discourses of the country as an ancient homeland. I ask whether these trips are a means of disseminating knowledge, and what forms of ignorance are assumed to prevail among the visitors that this “Divinity College” seeks to eliminate? Even more importantly, since the tours are state-sponsored, what ignorances are rendered possible, if not encouraged, at the cost of this selective knowledge dissemination? Drawing on fieldwork, I argue that the tours provide a space of encounter with what is presupposed as the visitors’ already acquired knowledge. On RN tours, both knowledge and ignorance are co-constitutive of the transformative power of pilgrimage, where ultimate knowledge is interpreted as putting the already-known-words into deeds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
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)0.0000.001

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 head0.040
GPT teacher head0.314
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