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Record W4402109688 · doi:10.55016/ojs/jet.v44i2.52249

Rendering Unto Caesar: Reconciling Liberal Principles With the Requirements of Roman Catholic School Board "Expectations for Graduates"

2018· article· en· W4402109688 on OpenAlexaffabout
James C. Lang

Bibliographic record

VenueJournal of educational thought. · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCatholicism and Religious Studies
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsRendering (computer graphics)Mathematics educationPolitical scienceSociologyPsychologyComputer scienceComputer graphics (images)

Abstract

fetched live from OpenAlex

I discuss potential ethical issues for an educator required by a publicly-funded Ontario (or similar) Roman Catholic School Board employer to teach students such that when they graduate they will be "discerning believer[s] formed in the Catholic Faith community who celebrate[s] the signs and sacred mystery of God's presence through word, sacrament, prayer, forgiveness, reflection, and moral living" (I 998, p. 5). I contrast the moral responsibilities of a Catholic religious studies educator with the moral responsibilities of a public school educator who is guided by principles of liberalism as characterized, primarily, by some of the works of Will Kymlicka.

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)0.015
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.041
Scholarly communication0.0100.005
Open science0.0010.008
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0030.001

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 head0.066
GPT teacher head0.304
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2018
Admission routes2
Has abstractyes

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