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Record W2995682562 · doi:10.51644/tdhl1580

Theology of “Person” with a Focus on Mental Health

2019· article· en· W2995682562 on OpenAlexaboutno aff
김경, Allen Jorgenson

Bibliographic record

VenueConsensus · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Society and Technology Trends
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousAnguishMental healthPerspective (graphical)State (computer science)PsychologySociologyPsychiatryEpistemologyPhilosophyArt

Abstract

fetched live from OpenAlex

In this article we consider a theology of “person” from the perspective of “mental health.” We first outline how a Lutheran theology of the person takes leave from the teaching of justification, which underscores that humans in healthy relationships are shaped by hope. We then outline the problem of mental well-being in Canada, with a higher than average percentage of people with mental health problems against global averages. This is especially noted among Indigenous populations. Using a case study based on a documentary film of an Indigenous youth, we note how people with mental illnesses reflect the state of society, even while these illnesses are predominantly understood individualistically. We explore how human brokenness is a communally shared experience, with Indigenous populations bearing a disproportionate share of the weight of collective anguish. Illumined by this Indigenous experience that affirms the relationality of all, we note how human suffering includes the suffering of the earth. In conclusion, we propose that the recovery of health for individuals demands attention to the mental health of society and the well-being of creation.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.043
Scholarly communication0.0050.006
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.289
Teacher spread0.271 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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