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Record W2995636073 · doi:10.1177/0008429819885615

Synergism between Catholicism and Indigenous Spirituality within the Drug Addiction Rehabilitation Program of Takiwasi, a Therapeutic Community in the Peruvian High-Amazon

2019· article· en· W2995636073 on OpenAlexvenueno aff
Alberto Dubbini, Marco Gallizioli, Fabio Friso, Jacques Mabit, Matteo Politi

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpiritualityIndigenousBiomedicineReligiosityAddictionAyahuascaAmazon rainforestTherapeutic communityPsychotherapistSociologyPsychologyAlternative medicineMedicineSocial psychologyPsychiatryAnthropology

Abstract

fetched live from OpenAlex

The association between spirituality and medicine is unfolding as a research theme that may have increasing practical implications in healthcare systems. Both spiritual and scientific dimensions are present within the treatment protocol for addiction applied at the Takiwasi Center, a pioneer therapeutic community that combines western approaches, including psychotherapy, biomedicine, and Catholic practices, with traditional Amazonian medicine. Through a series of open-ended and semi-structured interviews conducted on nine workers of the center during fieldwork research and comparison with the information obtained from literature review, the present article aims at testing the existence of an effective synergy between Catholic religiosity and indigenous-mestizo spirituality within the therapeutic process performed at the Takiwasi Center and puts in evidence some stimulating and problematic issues that arise from this synergy.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.416
Teacher spread0.346 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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