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Record W2409736518 · doi:10.21427/d7d43f

Ritual Journeys in North America: Opening Religious and Ritual Landscapes and Spaces

2016· article· en· W2409736518 on OpenAlexaboutno aff
Daniel H. Olsen

Bibliographic record

VenueArrow - TU Dublin (Technological University Dublin) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Tourism and Spaces
Canadian institutionsnot available
Fundersnot available
KeywordsReligious tourismPilgrimageGeographySociologyHistoryEthnologyAnthropologyAestheticsArchaeologyArt

Abstract

fetched live from OpenAlex

The religious landscape of North America is different from other regions of the world in that not only is there a lack of a highly visible religious elements, but also the idea and practice of pilgrimage and ritual travel is not as pervasive as in Europe and Asia. However, there are many human-built and natural spaces marked by Roman Catholics, Protestants, Mormons, Indigenous peoples, and members of other faiths which are subject to either formal or informal pilgrimage-like travel. Visits to these sacred sites have intensified with the rise and expansion of tourism after World War II, conflating pilgrimage-like travel with tourism. As such, there has been an expansion of the term ‘pilgrimage’ to describe the visits of people to sites of historical, political and/or pop culture importance. This paper examines the changing religious and ritual landscapes in North America, and examines the case of tourism and pilgrimage to Martyrs’ Shrine in Midland, Ontario, to show how ritual journeys in North America have become more inclusive over time.e become more inclusive over time.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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 designQualitative
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

Citations17
Published2016
Admission routes1
Has abstractyes

Explore more

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