Impact of Information and Communication Technologies (ICTs) in the Advancement and Empowerment of African Women
Bibliographic record
Abstract
During the past decade, global communications have changed dramatically, as a result of the increased use of information and communication technologies (ICT’s). ICT’s are becoming increasingly necessary if countries are to compete on a global scale. It has also been widely acknowledged that ICT’s have the potential to play an immediate role in the quest for sustainable and equitable development in Third World countries. ICT’s allow people to collect, store, process and access information and/or communicate with each other. How people in developing countries use these technologies to solve problems, organize their activities and realize their own objectives will determine the impact that these technologies will have in the course of their development. ICT’s are realities and concepts that have become unavoidable for anyone involved in issues of development and sustainability. However, access for women and especially rural women to ICT’s cannot be assumed to naturally occur. According to various authors and organizations most of the positive effect of the “information revolution” has bypassed women. It has not been easy to determine whether women have benefited from the information revolution. There is also the consensus that very little research has been done on women’s information needs and access to appropriate information in developing countries. It is therefore necessary to examine the impact that ICT‘s are having on women and whether or not they are serving women’s needs and preferences. It is also necessary to examine ways that policies can be put in place in order to assure that women have access to the technology, which is necessary to fulfill their information needs. This chapter, using case-studies from Africa, will examine the above issues.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".