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Record W2007305804 · doi:10.1080/02601370601151430

From sea to cyberspace: women’s leadership and learning around information and communication technologies in Coastal Newfoundland

2007· article· en· W2007305804 on OpenAlexaffabout
Darlene E. Clover

Bibliographic record

VenueInternational Journal of Lifelong Education · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCyberspacePublic relationsInformation and Communications TechnologyAgency (philosophy)Resistance (ecology)Citizen journalismGovernment (linguistics)SociologyEmpowermentPsychological resilienceEconomic growthPolitical scienceThe InternetSocial sciencePsychologySocial psychologyEconomics

Abstract

fetched live from OpenAlex

Due to a moratorium on the cod fishery in 1992, small, isolated coastal villages in Newfoundland suffer increasing unemployment, health problems and threats of re‐location by the government. In the hopes of addressing some of these problems, the Burgeo Broadcasting System (BBS) placed video‐conferencing and broad‐band internet into five small communities on the southwest coast. The purpose of our feminist participatory research process was to engage women in these communities in individual and collective discussions around the problems and potentials of these Information Communication Technologies (ICTs) in terms of learning, health, well‐being and economic resilience. We discovered the major problems are technical capacity and training, the top‐down implementation of the ICT process, indifference and a belief in the neutrality of technology. But we also uncovered a healthy resistance when and where it mattered, profound alacrity to using and learning the equipment if it meant a benefit to the community, a holistic pedagogical view and a strong sense of collective agency and responsibility. These have important implications for strengthening community‐based ICT education and research.

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)0.001
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 score0.237
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.274
Teacher spread0.253 · 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
Published2007
Admission routes2
Has abstractyes

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Same venueInternational Journal of Lifelong EducationSame topicInnovative Approaches in Technology and Social DevelopmentFrench-language works237,207