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Record W2516010505 · doi:10.3366/nor.2017.0126

‘Quite destitute and … very desirous of going to North America’: The Roots and Repercussions of Emigration from Sutherland and Caithness

2017· article· en· W2516010505 on OpenAlexaboutno aff
Marjory Harper

Bibliographic record

VenueNorthern Scotland · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationContext (archaeology)ScrutinyHistoryEstateAgency (philosophy)NarrativeSettlement (finance)Political scienceSociologyLawSocial scienceArchaeologyLiteratureArtEconomics

Abstract

fetched live from OpenAlex

This paper explores the roots and repercussions of emigration from the northern Highlands since the 1770s, through the lens of personal testimony, press accounts, estate papers, and recruitment agents' reports, along with some observations from novels and poetry. It studies the particular exodus from Scotland's two most northerly mainland counties – Sutherland and Caithness – within the wider context of Scottish emigration as a whole, and considers how settlement in Canada, the dominant destination, compares with the experiences of Highland emigrants elsewhere. The investigation has three sections, each of which follows a chronological path. It begins with the practical mechanisms through which emigration was promoted and implemented, and the attitudes that underpinned recruitment and sponsorship. The second section reflects on the attitudes of those who opposed emigration, while the third section dips into the emigrants' own testimony to analyse their motives and experiences. Overarching questions are the extent to which there were unique elements in emigration from the far north; whether the participants were passive victims in a process that was determined by others, or had agency, ambition and agendas of their own; and whether the narrative is characterised by continuity or change during the two centuries under scrutiny.

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 score0.281
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.235
Teacher spread0.206 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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