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Record W7020489116

Letter from the Secretary of the Interior, in answer to a resolution of the House of the 11th ultimo, transmitting report relative to the sale of certain Indian lands in Kansas.

2016· other· en· W7020489116 on OpenAlexaboutno aff

Bibliographic record

VenueSHAREOK (University of Oklahoma) · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLiberian dollarTreatyQuarter (Canadian coin)CherokeeSubject (documents)
DOInot available

Abstract

fetched live from OpenAlex

dated the 4th instant, and the papers therein referred to.In respect to the sale of the Cherokee neutral lands, I deem it proper to remark that by the terms of the treaty it is optional with the Secretary of the Interior to sell them in i!eparate tracts at not less than an average of $1 25 per acre, or in a body at not less than one dollar per acre.'he provision of the treaty for the sale in separate tracts is, that after the lands shall have been surveyed they shall be appraised at an average of not less than one dollar and a quarter per acre, exclusive of improvements, and after advertising for sealed bids, shall be sold to the highe~t bidder, for cash, in parcels not exceeding one hundred and sixty acres, and at not less than the appraised value.Another provision of the treaty authorizes the Secretary of the Interior to sell the whole of said lands not occupied by actual settlers, in a body, to any responsible party, for cash, for a sum not Jess than one dollar per acre.The sale in separate parcels, on sealed bids, is subject to the disadvantages of requiring years of time, and of leaving all the refuse lands in the hands of the Indians unsold.I did not ~oubt that an immediate sale in a body, at one dollar per acre, would be greatly more to the interest of the Indians than a tardy sale of the choice lands in separate tracts at the appraised value, with the inferior lands left undisposed of for years, and have, consequently, been desirous to find a purchaser who would take them all, good and bad together, at one dollar per acre.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.207
Teacher spread0.195 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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