Learning by Doing, Knowledge Spillovers, and Technological and Organizational Change in High-Altitude Mountaineering
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present an analysis of microlevel data from mountaineering on the 14 peaks over 8,000 m in height during the period 1895-1998. Prior to 1950, no expedition was successful in making an ascent and almost half of expeditions experienced a death, frostbite, or altitude sickness. By the 1990s, however, over half of the expeditions would successfully make an ascent and only about one in seven would experience an adverse outcome. Our objective is to distinguish between the effects of learning by doing and knowledge spillovers versus the effects of changes in technology or economic organization in explaining these results. As we can identify each climber by name and nationality, as well as each expedition team's methods and outcomes, we are able to disentangle the effects of learning at the individual, national, and international levels from effects due to improvements in climbing technology or changes in organizational methods and objectives. We find evidence that both individual learning by doing and learning through knowledge spillovers have contributed to the observed increase in ascent rates and to the decrease in death, frostbite, and altitude sickness rates.
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.
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 it