Bibliographic record
Abstract
Technological transformations are hard to grasp. Actors experiencing such transformations and academics studying them both struggle to understand the full meaning and impact of such changes because they fundamentally impact daily work and life. This dissertation explores how Danish seafarers experienced and made sense of the transition from sail to steam. The introduction and diffusion of steam power at sea was a pivotal turning point in maritime history. It shaped the historical reality for actors in the late nineteenth and early twentieth century and captured people’s imagination. So far, research on this process has primarily focused on technological invention, evolution, and implementation. Scholars have also explored national and regional diffusion patterns of steamships and their economic, organisational, and political consequences. However, how people experienced, made sense of, and engaged with the transition from sail to steam remains open. Guided by microhistory methodologies, I suggest studying the transition from sail to steam not as an abstract process but as a lived and narrated experience. Microhistory can grasp and contextualise significant societal and technological transformations by studying subtle and subjective experiences at the micro-level. This approach offers new insights into the relationship between labour, economy, and technology and complements existing economic history and ethnographic approaches in maritime research. By rebalancing structure and agency, I offer novel interpretations of the global transition from sail to steam and suggest a way to discuss large-scale transformations on a global scale through studies of lived experiences and individual agency.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.028 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".