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Record W7029522991

Journeying Together: Synodality and the Path Toward Social Salvation

2024· article· en· W7029522991 on OpenAlexaboutno aff

Bibliographic record

VenueProceedings of the Catholic Theological Society of America (Catholic Theological Society of America) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicChristian Theology and Mission
Canadian institutionsnot available
Fundersnot available
KeywordsPath (computing)Context (archaeology)Action (physics)Social relationship
DOInot available

Abstract

fetched live from OpenAlex

The unfolding process of the Sixteenth Ordinary General Assembly of the Synod of Bishops, or the Synod on Synodality (2021Synodality ( -2024)), offers an unprecedented opportunity for theologians to rethink their engagement in the church and society.Aware that several CTSA members participated in the Roman meetings of the Synod in 2023, this special invited session convened two of the synod participants (Maria Cimperman and Agbonkhianmeghe E. Orobator) to share insights with peers in the Society.Our session also benefited from the presence of Catherine Clifford (St.Paul University, Ottawa) who briefly shared her experiences at the synod and invited society members to her paper later in the conference, presented in the Synodality Interest Group.C. Vanesa White graciously read a brief paper from Cimperman, who was in Rome for the drafting of the synod's Instrumentum Laboris.Her paper illuminated some lessons from the first session of the synod and focused on participation and coresponsibility as the most important fruits of the synod so far.Orobator's presentation addressed some of the pitfalls and opportunities of this "experiment in ecclesiology.""How," he asked, "do we actually journey together as a reconciled community?"Following the two presentations, the participants split into six small groups.Dr. Ahern introduced the conversations in the spirit method and facilitated three rounds of listening on the following questions:

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.022
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.248
Teacher spread0.222 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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