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Record W2766551486 · doi:10.15402/esj.v3i1.239

Educating Men-and-Women-for-Others: Jesuit and International Educational Identity Formation in Conversation

2017· article· en· W2766551486 on OpenAlexvenueno aff
Christopher Hrynkow

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsnot available
Fundersnot available
KeywordsSolidaritySociologyGlobal educationGender studiesPublic relationsPedagogyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In a globalising world that often appears overrun by corporate and consumerist values, international education can be tempted to follow suit and support elitist transnational learning. Such an outcome may emerge intentionally or through an unreflective embrace of an unjust status quo. It follows that students and alumni of international education institutions may have little concern for more broadly communitarian values such as social justice, solidarity, and active care for those on the margins of local and global societies. However, for those craving alternatives that counteract segmented interests, this article demonstrates one such alternative. It maps how ‘men-and-women-for-others,’ a concept with worldwide traction in Jesuit education, can both inform and learn from international education concepts and practices. Further, this article employs the case of two remarkable Jesuit nativity schools to ground that dialogical process of meaning making, as men-and-women-for-others interacts with the International Education Studies literature in a mutually enhancing manner. The results will be of interest to those committed to fostering social justice, solidarity-based action, and a glocal ethic of care amongst the students and alumni of both Jesuit and international educational institutions.

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)0.012
metaresearch head score (Gemma)0.010
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0310.056
Scholarly communication0.0140.014
Open science0.0020.018
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.179
GPT teacher head0.478
Teacher spread0.298 · 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
Published2017
Admission routes1
Has abstractyes

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Same venueEngaged Scholar Journal Community-Engaged Research Teaching and LearningSame topicReligious Education and SchoolsFrench-language works237,207