Impacts of climate change on food system security and sustainability in Bangladesh
Bibliographic record
Abstract
ABSTRACT Climate change poses a significant threat to the security and sustainability of global food systems, particularly in vulnerable regions such as Bangladesh. This paper comprehensively reviews the impact of climate change on food system security and sustainability in Bangladesh. Specifically, it examines the country's food system and, the climatic conditions endangering food systems and associated vulnerabilities. A systematic review methodology was adopted to select the relevant literature, based on predefined inclusion criteria and research questions. To mitigate selection bias, the research team independently screened and evaluated the articles for inclusion in the review process. Our review reveals increasing trends in temperature fluctuations and irregular rainfall occurrences, posing significant challenges in terms of crop management and planning. The occurrence of floods due to extreme rainfall and sea-level rise exacerbates food insecurity in affected areas. Additionally, moderate to severe droughts have been identified in some regions. The paper also evaluates the effectiveness of current adaptation initiatives and the degree of integration among relevant stakeholders. Through this analysis, the paper emphasizes the importance of local climate-change adaptation strategies and stakeholder collaboration in mitigating the adverse impacts of climate-change on food system security.
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 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".