The ICTs, climate change adaptation and water project value chain
Bibliographic record
Abstract
Water resources are one of the cornerstones of socioeconomic development, and as such, they are central to understanding climate change impacts on vulnerable populations.Emerging research at the intersection of climate change, information and communication technologies (ICTs) and development indicates the existence of increasing linkages between use of ICT tools and developing country efforts to mitigate, adapt, monitor and strategise in the face of climate change.Critical resources such as water are at the forefront of developing countries' adaptation agendas.This paper maps conceptually the linkages between climate change adaptation, water and ICTs, drawing on various approaches from the development, ICTs, and climate change fields 1 .It presents a conceptual tool that can be used by ICT and climate change practitioners and researchers seeking to analyse and plan field interventions in contexts facing water stress due to short and longterm climate change.The 'ICTs, Climate Change Adaptation and Water Project Value Chain' maps a processfocused approach for integration of ICT tools into the design, operation and evaluation of projects in the field of climate change adaptation and water resources.It will be argued that, while ICTs have the potential to enable adaptive capacities and actions for water resources under climatic stress, their role needs to be integrated into ongoing and future initiatives from a holistic perspective one that considers the complete 'project value chain'.Ultimately, projects in the field should ensure not only the availability, affordability and accessibility of ICT tools (all aspects of "digital capital"), but also their actual uptake and use if adaptation goals and ultimately, development outcomes, are to be achieved.The analysis will suggest that integrating this 'hybrid' processfocused approach into the design, operation and evaluation of wateradaptation projects, could help build the adaptive capacity of vulnerable communities to climateinduced shocks and chronic trends.This document was prepared building on the findings of three regional reports commissioned by the International Development Research Centre (IDRC) and the Association for Progressive Communications (APC) on ICTs, Climate Change and Water from
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".