MétaCan
Menu
Back to cohort
Record W2950168464 · doi:10.7202/1060951ar

Proposing an Examen for Living the Ecology of Daily Life and Building a Culture of Care

2019· article· en· W2950168464 on OpenAlexvenueno aff
Damien Marie Savino

Bibliographic record

VenueThe Trumpeter · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyScale (ratio)Industrial ecologyActivities of daily livingSociologyPsychologyBiologyGeographySustainability

Abstract

fetched live from OpenAlex

This article examines a relatively unexplored aspect of integral ecology in Laudato Si’ called “the ecology of daily life” and considers how living a healthy ecology of daily life relates to the unique vocation of humans to care for creation. Specifically, what does the Pope intend by “the ecology of daily life”? What are some obstacles to living it? How can living the ecology of daily life help build a culture of care? Based upon the principles articulated in the encyclical, the article proposes an examen for assessing progress in living the ecology of daily life. This examen is applied to two case studies in order to discern a fruitful practice of the ecology of daily life. The case studies represent environmental situations that, while affected by larger scale industrial/commercial processes, are primarily driven by micro-scale decision-making and small daily actions of individuals and local communities. The first case study focuses on endocrine disrupting chemicals as an example of a polluted ecology of daily life, and the second highlights a zero waste initiative as an exemplar of an integral ecology of daily life. The article concludes with comments on lessons learned from the exercise of applying the examen to two concrete situations. This approach can help individuals and communities discern how to build a culture of care based upon the principles of the ecology of daily life as they are presented in Laudato Si’.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.322
Teacher spread0.299 · 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 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueThe TrumpeterSame topicReligion, Ecology, and EthicsFrench-language works237,207