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Record W7066218125

George Crawford fonds, 1813-1868, n.d.

2021· other· en· W7066218125 on OpenAlexaboutno aff

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2021
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)State (computer science)ThursdaySupperTourismBaton rouge
DOInot available

Abstract

fetched live from OpenAlex

Most of the fonds consists of correspondence written to George Crawford, a Pennsylvania State Legislator. The bulk of these letters were written to him while he was serving as a Pennsylvania State Legislator from 1831 to 1834. Other materials include rolls for labourers working on the Pennsylvania Canal, legal documents, accounts, printed material, receipts, and newspapers. Correspondence, 1817-1868, n.d. Contains 268 letters. Many of the letters are from constituents, fellow legislators, judges, and lawyers who were looking for Crawford’s support on their bills, need for a charter, petitions, remonstrances, or inquiries. An interesting letter to George Crawford from his son R.A. Crawford in 1857 provides a detailed description of his trip to Niagara Falls, including sightseeing excursions to Goat Island, the suspension bridge, Barnett’s Museum, and Lundy’s Lane. June Saturday 14th 1857 Father, I suppose you would like to hear from us concerning our journey. I suppose to give you a full history of our journey I must commence from the time we left home. We had a tolerable pleasant trip on packet to Williamsport. Rather cool arrived at Williamsport about eleven o’clock laid by until 3 after dinner and took the cars for Elmira arrived about ten at night took our supper went to bed, next morning started to the great Niagara, arrived at Niagara about eleven o’clock went over to Gote Island to view the falls. We saw a great many curiosities. Gote Island is heavily timbered and would be a beautiful place of retreat in the hot summer months, for those that have but little to do and plenty to spend. After viewing the falls, we left the Island for dinner, after dinner we was pestered by a fellow that wanted to haul us over the great and beautiful suspension bridge to view the falls from Canada side, at length he offered so cheap and agreeing to pay the toll we took him up at his bargain. He said he must have his pay before he started after collecting his money said that his brother should take us. So, we mounted the cab and off we went for the bridge arriving there the collector demanded his toll, the driver said we was to pay it we said the driver was to pay the toll, so we sat and argued about the matter and had some sport with the fellow. We told him that he should either take us back or pay the toll at length he paid and over we went to the fall. After viewing the falls, we went to see a museum they have there that is quite a curiosity. They have animals of different descriptions, birds and fish, snakes and a great many curiosities made by the Indians such as moccasins, bark canoes, powder horn, and a great many other things made by the squaws. After seeing the different things in the museum, we walked out into an adjoining lot to see the wolves and buffaloes. The buffaloes appeared to be very savage, after seeing the animals we mounted our seats and told the driver to drive us out to Lundy’s Lane battleground. At first he refused. Andrew told him to throw down the lines and he would drive himself, at length he drove us out there. They have a pair of winding stairs we walked up and took a view of the country and of the surrounding scenery. After viewing the beautiful farms for there is such there, we left for the bridge, took supper near the bridge with a dutchman, took the evening train for Detroit…”

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.374
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3740.197

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.

Opus teacher head0.018
GPT teacher head0.166
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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