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Record W2243436006

How Women in Remote and Rural First Nation Communities are Using Information and Communication Technologies (ICT)

2014· article· en· W2243436006 on OpenAlexaffvenueabout
Penny Carpenter, Kerri Gibson, Crystal Kakekaspan, Susan O’Donnell

Bibliographic record

VenueJournal of rural and community development · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsInformation and Communications TechnologyThe InternetRural areaPublic relationsBusinessEconomic growthPolitical scienceSociologyWorld Wide WebComputer science
DOInot available

Abstract

fetched live from OpenAlex

First Nations women have a strong role guiding the success of their family and their community. In the past, women nurtured their family, ensuring their food and safety. These responsibilities are still true today with the added challenges and opportunities of modern day life. In Northern Ontario, many remote and rural First Nation communities are connected to integral services via broadband. The current study explores how First Nations women are using information and communication technology (ICT) and if the technology can address some of their challenges and open up new opportunities. Two hundred and thirty one women living in remote and rural First Nation communities in Northern Ontario completed an online survey, sharing their thoughts and experiences with regard to: ICT use in daily life, ICT for health and wellness, ICT for cultural preservation, and what is needed to support their effective use of ICT. The findings suggest that the women in these remote communities are active users of ICT, using the internet for frequent communication with people living in their own communities along with other communities and elsewhere in Canada. The women are also familiar with telemedicine, use the internet in a variety of ways to preserve their culture, and identified many strategies for supporting their effective use of ICT. Finally, we explore a case-study of how women in Slate Falls First Nation are using ICT.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.001
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 head0.035
GPT teacher head0.215
Teacher spread0.180 · 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 designOther design
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

Citations11
Published2014
Admission routes3
Has abstractyes

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