The Little Ice Age: The History and Future of a Traveling Concept
Bibliographic record
Abstract
ABSTRACT First coined in the 1930s, with reference to glaciation in North America, the concept of the “Little Ice Age” has undergone continuous revisions. It has traveled academically from glaciology to climatology, archeology, history, and, most recently, climate communication. Over time, it has grown into one of the most discussed topics in the field of climate history and attracts both considerable scholarly interest and public attention. The term “Little Ice Age” has been criticized for oversimplifying climatic change, focusing too much on temperature, and excluding possible effects on humans. Yet it remains a powerful “boundary object” in interdisciplinary cooperation, science communication, and the “environing” of history. In this sense, it serves similar functions as other concepts in the field of human–environment interactions, such as “global warming” or “climate resilience.” This article investigates the contested history and the potential uses of the “Little Ice Age” concept. It explores how the concept encourages interdisciplinary consilience, global perspectives, and public debate. In summary, these aspects are connected and contrasted to the use of similar concepts, such as “climate resilience” and “tipping points” in the sphere of climate–society interactions. This article is categorized under: Climate, History, Society, Culture > Major Historical Eras Perceptions, Behavior, and Communication of Climate Change > Communication Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".