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Record W2947065456 · doi:10.15365/joce.2201052019

Teaching While Praying, Praying While Teaching: An Interactional Sociolinguistics of Educational Prayer

2019· article· en· W2947065456 on OpenAlexaff
Robert Jean LeBlanc

Bibliographic record

VenueCatholic education/Catholic education (Dayton, Ohio. Online) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPrayerContextualizationLinguisticsSociolinguisticsPsychologySociologyPedagogyInterpretation (philosophy)TheologyPhilosophy

Abstract

fetched live from OpenAlex

What are the linguistic resources for teachers who pray in contemporary Catholic school classrooms? This article considers the intersections of prayer and language practice, and I make central two arguments. The first is that educational prayer—a particular type of teacher-led extemporaneous prayer in Catholic schools—is a linguistic phenomenon, a highly-flexible set of linguistic resources, captured within a special interactional frame marked by ambiguous boundaries which contains both prescribed formulaic linguistic properties and those which allow the performer to attend to real time classroom contingencies. Drawing on interactional data from a Catholic school classroom, this article delimits the contextualization of linguistic signs during prayer: how teachers indicate the connection between their words and the sociocultural frameworks which are relevant for that action. The second is that both interactional sociolinguists and Catholic school researchers would greatly benefit from attending to these linguistic features, from seeing prayer unfold in real-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 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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.384
Teacher spread0.349 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations3
Published2019
Admission routes1
Has abstractyes

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