An Integrated Approach for Evaluating Adaptation Options to Reduce Climate Change Vulnerability in Coastal Region of the Georgia Basin
Bibliographic record
Abstract
This paper presents an integrated approach that integrates climate change impact assessment/vulnerability identification, adaptation option evaluation, and multi-stakeholder participation. The integrated approach was applied in the Georgia Basin (GB) for identifying desirable adaptation options to reduce climate change vulnerabilities. Different computer-based and non-model based methods were adopted to form the integrated approach. These tools include environmental simulation modeling, geographical information system (GIS), internet multi-stakeholder consultation, and multi-criteria decision making (MCDM). The research started with the identification of vulnerabilities of ecosystems, coastal areas, and economic sectors to climate change. This was followed by an online survey and interviews that allow stakeholders to conduct a multi-criteria evaluation of adaptation options. The analytic hierarchy process (AHP), an MCDM technique, was adopted to develop an adaptation evaluation tool to identify the priorities of sustainability goals/indicators and to rank desirability of adaptation options. The case study in the Georgia Basin of Canada provides some articulation on how the integrated approach can provide an effective means for the synthetic evaluation of the general desirability levels of a set of adaptation options through a multi-criteria and multi-stakeholder decision making process. Thus, the study contributes to the science on adaptation option evaluation. While the case study identified and evaluated a number of adaptation options to deal with potential vulnerabilities to climate change in several key sectors in the region, this paper focuses on sea level rise (SLR) impacts and adaptation options for the coastal region management. The completed research results of the case study are described in the final report submitted to Climate Change Action Fund of Canadian Government (Yin, 2001).
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".