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Record W1932395030

Archaeological Surveys Two Black Communities, 1998 Surveying Tracadie Area Testing in Birchtown (Curatorial Report #92)

2000· article· en· W1932395030 on OpenAlexaboutno aff
Stephen Powell

Bibliographic record

VenueNova Scotia Museum · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaArchaeologyPopulationSettlement (finance)ExcavationHistoryGeographyGenealogyEthnologyDemographySociology
DOInot available

Abstract

fetched live from OpenAlex

Birchtown, Nova Scotia, was founded by Black Loyalists in 1783 and was the largest and most significant settlement of free Blacks in North America. Although its population grew rapidly, Birchtown did not thrive. The discrimination and inequity the Black Loyalists had hoped to escape followed them to Nova Scotia. In 1791 their discontent led half of Birchtown's population to join the exodus for Sierra Leone in West Africa, an event from which the settlement would never recover. The archaeological study of the Birchtown area began in 1993 and has continued every year since that time. The objectives of the 1998 project were three-fold: the excavation of AkDi-23, thought to be the home of Stephen Blucke; formal testing of AkDi-6 to confirm that it dated to the eighteenth century; and, the bisection of an enigmatic rock mound, one of a series of 22, at AkDi-21. The latter two projects are the subject of this report. _____________________________________________________________________ Please note: This resource is presented as originally published. The content of older reports may not reflect the current state of knowledge on the topic documented. Please be aware of this when using this resource.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.551
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.145
GPT teacher head0.336
Teacher spread0.191 · 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.

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

Citations2
Published2000
Admission routes1
Has abstractyes

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