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
In these files, there have been numerous photographs showing ships engaged in the fishing trade, \nthe salmon trade, and the lumber trade. The last days of commercial sail were filled with three \nproblems that grew to overwhelming proportions: a labor problem, a paying freight problem \n(how does the ship pay its way?), and the biggest problem of them all—competition from more \nefficient systems, whether rail or powered ship. When compound steam engines became the \nnorm, rather than the exception, commercial sail could no longer compete with known arrival \nschedules and rapid turn-around time. Instead, sail could compete best with bulk cargoes where \nfree warehousing (several months in the hold of a sailing ship) was the norm. From the 1880s \nthrough the 1920s, another persistent challenge was to find a crew with a skill set commensurate \nwith the rigors of a large sailing vessel. The smart able-bodied sailors opted for the easier life in \nsteam. While there was no want of capable officers, the lack of competent sailors became \ncritical well before 1900. In a brief article I read from the San Francisco Call Bulletin around \nthe turn of the century, there was a brief newsy note about a well-known master of a big 4- \nmasted bark that was “day sailing” around the Bay trying to get his newly-hired (shanghaied?) \ncrew into some sort of sail-drill shape before venturing forth on a voyage. While that kind of \ntraining is laudable, it is also revealing of the lack of sailing fundamentals available wharfside in \nlatter-day sail. \nWhat were the cargoes available to sail in its latter days? Photograph 106a, a colored postcard, \nis illustrative. Front and center is a French-built bark at the coal wharves in San Francisco south \nof Market Street. Sailing ships routinely carried coal up and down the west coast and across the \nPacific and it was a paying “retirement” trade for older sailing vessels. The historic clipper \nDashing Wave was a particularly fetching coal tramp in its latter days and there are several \nphotographs of this clipper in and around San Francisco hauling coal long after the glory days. \nIronic that sailing ships carried the fuel that nourished the boilers of steam engines that were \nputting the windships out of business. However, such was the reality. \nGrain was another bulk cargo, and odd as it may seem now, California was once a world \nbreadbasket for grains of several kinds. Wooden ships carried the wheat through the 1870s and \n1880s back to the east coast. Starting in the 1870s, European (primarily British, but not \nexclusively so) sailing ships loaded wheat for Europe and by the end of the 1880s dominated the \ntrade. \nPhotographs 106b and 106c are of another boom bulk cargo that lasted well into the twentieth \ncentury and still prevails—lumber. Photograph 106b shows Port Blakely, Washington, awash in \nlarge latter-day sailing ships loading finished lumber for ports all around the world. The Hall \nBrothers maintained an important shipyard co-located with Port Blakely. Sailing ships hauled \nfinished and semi-finished lumber to Hawaii, Australia, and all over the Pacific. The streams of \nlumber ships after the 1906 earthquake and fire were prodigious. Photograph 106c (taken 26 \nJuly 1910) reveals, even though faded, large sailing ships (and a steamer to the right) loading \nlumber from the Hastings Mill at Vancouver, British Columbia.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.057 |
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