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Record W7062367525

WORDS, BRICKS AND DEEDS: THE FOUNDATIONS OF HOME RULE IN THE BRITISH-AMERICAN COLONIES

2018· dissertation· en· W7062367525 on OpenAlexaboutno aff

Bibliographic record

VenueWakeSpace Scholarship (Wake Forest University) · 2018
Typedissertation
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementCharterSettlement (finance)IndigenousState (computer science)ColonialismGovernment (linguistics)Estate
DOInot available

Abstract

fetched live from OpenAlex

The legal and cultural tension between cities, towns and state government, characterized as the question of home rule, has existed since the creation of the Republic. The founding of the New World required the creation of new settlements and these settlements serve as an example of settler’s interest in home rule. This thesis examines the founding of nine communities in British North America: Dedham and Sudbury, Massachusetts; Exeter, New Hampshire; New Haven, Connecticut; Albany, New York; Germantown and Carlisle, Pennsylvania; Savannah and Ebenezer, Georgia. Evidence from charter documents, colonial legislation, writings, town plans and secondary resources, such as the published history of towns, is used to explain how the “words, bricks and deeds” of settlers give evidence of their home rule. It provides background on other settlements, including Spanish, French, indigenous and maroon communities. The interdisciplinary analysis is given in contrast to the analysis of the legal doctrine commonly known as “Dillon’s Rule.” It closes by examining the larger issue of the changing nature of municipal, as opposed to private, corporations. The thesis looks at the settlement of the Northwest Territories, or present-day Ohio to describe how the federal and state government replaced the colonial authorities and exerted control of municipal corporations bringing us to our current state of tension.

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)0.000
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 score0.106
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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
Published2018
Admission routes1
Has abstractyes

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