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Record W7033276457

Q&A: Women, information access and rural development

2004· other· en· W7033276457 on OpenAlexaboutno aff

Bibliographic record

VenueCGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) · 2004
Typeother
Languageen
FieldDecision Sciences
TopicForecasting Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPaceRural areaRural managementInformation accessActive listeningGovernment (linguistics)Access to informationPublic accessRural developmentPhysical access
DOInot available

Abstract

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How can women participate in and influence rural development policy in the information society?\n\nWomen must be leaders at many different levels of society. In their own homes they influence the direction and pace of rural development by educating their daughters and sons. Women stress the importance of education, and often devote most, if not all of their incomes to their children´s school fees. This priority-setting among women has had a measurable impact in rural societies around the world. Governments and society in general must ensure that the efforts of ordinary women to educate their children are not in vain.\n\nWhat kind of information services should be provided to rural women?\n\nThe provision of information to women is less important than ensuring equitable access to information. The vast majority of non-literate people are women who live in rural and remote areas of the world. Most information services do not reach rural women, and those that do are driven by an agenda that rural women have not had a hand in defining. Information in written form and unfamiliar languages is not accessible to them. Face-to-face communication through women´s organizations and radio, especially through radio listening groups, are two of the most successful sources of information for rural women.\n\nWhat are the most appropriate public access points for women?\n\nCulture will determine the best public access points for women in a particular society. In Kenya, for instance, health clinics, churches and women´s self-help groups have historically been important information access points. In Jamaica, adult learning centres and women´s business associations have been successful in responding to women´s information needs. Community radio stations that broadcast specific programmes in local languages have been successful in countries such as Ghana. It is also very important that information access points are supplemented by programmes that offer learning opportunities for women, such as literacy courses, mother/child health care programmes or business support.\n\nHow can women´s traditional and indigenous knowledge contribute to content development efforts?\n\nThere are many ways in which women´s indigenous knowledge can contribute to efforts to develop content for information and communication programmes. One good example is the series of radio programmes in Ghana. Each month the programme focuses on a different indigenous food and discusses with women its production, processing, nutritional advantages and marketing possibilities. Another interesting example comes from India, where the Honey Bee Network (see www.sristi.org/index.php) is compiling local farmers´ innovations in an online database, ensuring to some extent the preservation and dissemination of local knowledge. \n\nThere is some doubt, however, that women´s participation in content development will be enough to ensure that women actually benefit. In Namibia, for instance, a new hybrid variety of millet was named after the leader of the women´s group that participated in the plant breeding and who shared the local germplasm with scientists. Yet it is questionable whether this has truly ´empowered´ the women. Did the women gain financially or in any other way from this exchange of their indigenous know-how? Women´s organizations are now arguing that they must not lose the power associated with their indigenous knowledge and risk its appropriation. This is one reason why the example of the Honey Bee Network in India will likely be championed in other parts of the world. \n\n\nmailto:hhambly@uoguelph.ca \n\n\nHelen Hambly Odame has more than 12 years´ experience in international R&D programmes in Africa and Latin America. She is currently Assistant Professor in Rural Extensions Studies at the School of Environmental Design & Rural Development (SEDRD) at the University of Guelph, Canada.

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)0.006
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.001
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 head0.150
GPT teacher head0.434
Teacher spread0.284 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2004
Admission routes1
Has abstractyes

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