Adaptive Social Protection: A Systematic Literature Review and Research Agenda
Bibliographic record
Abstract
Adaptive social protection represents a novel form of approach that is more holistic in addressing issues related to disasters associated with climate change and social shifts. Adaptive social protection has resurfaced social protection as a new approach to assist an individual or society to mitigate vulnerability or potential harms related to poverty and climate change. Despite the necessity for enhanced comprehension of adaptive social protection approaches, there exists a dearth of scholarly research on this subject. This study strives to address this gap. Therefore, the primary objective of this research is to map the gaps in studies related to the topic of adaptive social protection, thereby enabling us to identify future research agendas. Through this article, we systematically review existing studies in social adaptive protection within two decades. 305 articles are categorized and analyzed using the SPAR-4-SLR protocol by Paul (2021) and employs the VosViewer 16.1.19 to scrutinize and dissect this topic in a bibliometric approach and map the distribution on authorship, countries, institutes, and keywords. We found that the existing publications in adaptive social protection primarily originated from the United States, United Kingdom, and Canada. By synthetically analyzing the keywords, the dominant hot spot of adaptive social protection research could be concluded as “adaptive management”, “climate change”, or “adaptation”.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".