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Record W1966045565 · doi:10.3138/tjt.21.1.15

The Meeting of the Rivers: Being Native and Christian in Canada

2005· article· en· W1966045565 on OpenAlexvenueaboutno aff
Achiel Peelman

Bibliographic record

VenueToronto Journal of Theology · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpiritualityHonourWitnessGospelProclamationReligious pluralismTheologySociologyFaithEcumenismEvangelismEcclesiologyReligious studiesChristianityContext (archaeology)Pluralism (philosophy)PhilosophyLawHistoryPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

Since the end of the Second Vatican Council, religious pluralism has become the unavoidable context for any serious reflection on Christian theology and spirituality. The Roman Catholic Church and many other Christian denominations now consider dialogue with the other religions and spiritual traditions as a constitutive dimension of their mission, even though the relationship between the proclamation of the Gospel, the main objective of mission, and dialogue remains a controversial question. In this article, written in honour of Jesuit theologian Carl Starkloff, I would like to reflect on how this evolution affects the First Nations peoples of Canada. As both a participant and a theological observer, I have been able to witness their commitment to the development of their own Christian communities as well as their efforts to build bridges between their traditional spirituality and the Christian faith. My reflections are inspired by regular meetings with aboriginal persons at the Anishinabe Spiritual Centre in Anderson Lake, Ontario, a place where Carl Starkloff is remembered as a great theologian and spiritual companion.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.092
Threshold uncertainty score0.671

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0630.013
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.271
Teacher spread0.260 · 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

Citations1
Published2005
Admission routes2
Has abstractyes

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