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Record W2165810804 · doi:10.18061/1811/63999

Living on the Edge: Old Colony Mennonites and Digital Technology Usage

2015· article· en· W2165810804 on OpenAlexaffabout
Kira Turner

Bibliographic record

VenueJournal of Amish and Plain Anabaptist Studies · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsYork University
Fundersnot available
KeywordsEnhanced Data Rates for GSM EvolutionGenealogyInternet privacyGeographySociologyComputer scienceHistoryTelecommunications

Abstract

fetched live from OpenAlex

Mainstream society's perceptions of traditional Mennonites tend towards viewing them as technologically deficient. Yet, cell phones, computers, and tablets are increasingly prevalent within this population. Challenging stereotypes, this article considers digital technology usage by Old Colony Mennonites (OCM) in Southwestern Ontario (SWO). Rooted in the Anabaptist tradition, a lengthy history of migration led the OCM to settle in Mexico. Yet, due to economic circumstances, many continue to travel to and from SWO, resulting in a transformation; from maintaining an isolated lifestyle to one that includes some form of mainstream society. This shift includes digital technology usage, specifically texting, social media, and the Internet. Although research into Mennonite technology practice exists, these new forms of digital technologies have not received similar attention. Drawing on fieldwork conducted in 2012, this study took place in five Old Colony communities in SWO. Interviews, with both former and current OCMs, and others who have some connection to the Mennonites, suggest that the Old Colony navigate the lines between prescribed values and twenty-first century requirements in terms of a continuum, on their own terms. While digital technologies may create tensions within the community, they also act to blur lines between geographical boundaries, extend social networks, and allow OCMs to create their own vision of the society in which they wish to live.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.231
Teacher spread0.203 · 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

Citations4
Published2015
Admission routes2
Has abstractyes

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