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Record W1508387889

Harnessing Information and Communication Technology to Build an Online Community of Northern/Rural Women

2005· article· en· W1508387889 on OpenAlexvenueno aff
Dawn Hemingway, Christina McLennan

Bibliographic record

VenueCanadian women's studies · 2005
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationGeographyLife expectancyPovertySocioeconomicsGovernment (linguistics)Rural areaEconomic growthSociologyPolitical scienceDemography
DOInot available

Abstract

fetched live from OpenAlex

Northern British Columbia (BC) is avast geographic area covering almost 600,000 square kilometres, with a population density ofless than one person per square kilometre. Less than 50 per cent of the 300,000 people residing in northern BC live in communities with a population of more than 10,000 people with the remaining living in communities of less than 5,000 people (Province of British Columbia). Given its geography, demographic features, and lack of proximity to the lower mainland, receiving appropriate health and social services in northern BC can be a challenge. Regardless of geographical location, women already face a disproportionately negative impact from poverty, violence, and economic inequality (Lippman, 1998; Lock, 1998). For northern women, this challenging situation is further complicated by geographic, social, and cultural isolation; lack of access to basic needs, appropriate housing and employment; uncertain resource-based economies; and lack of appropriate health and social services (Leipert; Leipert and Reutter 2005; Madrid). In fact, women living in the North, have a life expectancy that is four years less than their southern counterparts (British Columbia Provincial Health Officer). The detrimental effect of these negative factors increases manifold when coupled with issues related to culture, sexual orientation, abilityldisability, age and race (Leipert and Reutter 1998). T o further compound the situation, recent (and ongoing) government cuts to health and other social services have caused increased hardship for many northern and rural communities in British Columbia. T o overcome obstacles related to inequality and injustice resulting from living in a northernlrural setting, a group of women from across northern BC have come together to develop the Women North Network (WNN)-a primarily web-based network that harnesses information and communication technology (ICT) as a tool to connect women around issues of common concern. W N N allows women, who might otherwise have no way of coming together, to share experiences, information, and resources. Its formation has made it possible to build an online community aimed at addressing rural women's issues by overcoming barriers (e.g., distance, climate, prohibitive travel costs or non-existent public transportation, etc.) that isolate women in their geographic community-barriers that tend to confine and limit focus to local (often crisis oriented) concerns. Through connecting across the region, women are coming to recognize that local concerns about the health and wellbeing of their communities and families have larger structural, systemic implications that need to be addressed collectively and beyond narrow geographic confines.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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 designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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