Bibliographic record
Abstract
The transformational changes brought about by the Internet stimulate the planning of social and economic development in networked communities. This chapter will cover the following topics: • The community and its economic and social development; • The importance of development strategies and theory: ° An introduction to types of strategies and theories ° The influence of ICTs on community development • Strategic planning in a community: ° An outline of strategic planning ° The role of ICTs in the strategic planning process; ° Examples of ICT community development opportunities; • Key success factors in implementing a community development strategy; • Evaluation and measurement of community development. The strategic inclusion of information and communication technologies (ICTs) within community development plans can be compared to organisational re-engineering. They both require effort to become more efficient, and novel perspectives are needed to develop new economic values. Within the broad context of the human condition, they both involve understanding what people need and want, how inequities can be bridged, and how to minimise the negative impact of making changes. A lesser approach runs the risk of communities resolving one challenge only to see new problems spring up. As was aptly put by Matthiessen, Schwarz and Find (2006), “[Creation] of wealth in an economy of ideas is derived far less than we imagine from the technological hardware and infrastructure. Rather it is dependent upon the capacity to continually create content or new forms of widely distributed knowledge for which there is a need to invest in human capital throughout the economy” (p. 15). Information technology has acted as an important trigger for the development of business process re-engineering in firms (Attaran, 2004), and ICTs have had a similar impact on communities—they expand the need to keep up with global changes. Innovative use of IT has led many firms to develop ways of more effectively coordinating their activities and at lower costs, thus giving them strategic advantages. Similarly, communities around the world are paying attention to the Internet economy, realising that it is a source of opportunity that also presents many challenges. Firms and communities are often linked; as more businesses participate in work that is network-intensive, local communities have the opportunity to learn how they too can grow and change as a result of being networked, or at least learn to be a supportive ally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".