Dichotomy or continuum? A global review of the interaction between autonomous and planned adaptations
Bibliographic record
Abstract
Adaptation to climate change is often conceptualized as a dichotomy, with responses being either planned (formal and structured) or autonomous (organic and self-organized, often known as “everyday adaptation”). Recent literature on adaptation responses has highlighted the existence and importance of the interplay between autonomous and planned adaptation, but examination of this interaction has been limited to date. We use a global database of 1682 peer-reviewed articles on adaptation responses to systematically examine autonomous and planned adaptations, with an emphasis on how these types of adaptations interact with one another. We propose a third category, mixed adaptation, which demonstrates characteristics of both autonomous and planned types, and which recognizes nuances in how organization, external support, formality, and autonomy manifest in the fuzzy space between the two. We find that more than one-third of articles reporting on adaptation responses fall into this mixed category, with cases across sectors and world regions. We develop a qualitative typology of mixed adaptation that identifies nine ways that autonomous and planned adaptation interact and influence each other both positively and negatively. Based on these findings, we argue for more nuanced examinations of the interplay between autonomous and planned adaptation and for conceptualizing adaptation planning as a continuum between the two rather than a dichotomy. Exploring the patterns of interplay from a large database of adaptation responses offers new insights on the relative roles of both autonomous and planned adaptation for mobilizing adaptation pathways in locally relevant, scalable, effective, and equitable ways.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.021 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".