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Nimble Fingers and Strong Backs

2017· book· en· W4252022188 on OpenAlexaboutno aff
Sherry Farrell Racette

Bibliographic record

VenueUniversity of Illinois Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousReciprocity (cultural anthropology)WoodlandProvisioningGeographyFur tradePolitical scienceEthnologyHistorySociologyEconomic historySocial scienceEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

In many regions of Canada, from the fur trade to the twentieth century, aspects of Euro-Canadian economies have been dependent on a pool of female Aboriginal laborers. This chapter suggests that the “harsh reality” of northern plains and woodlands survival pushed traders into relationships with indigenous women, perhaps initially as companions and helpmates, but increasingly cognizant of women's seasoned proficiencies in harvest and provisioning as well as the tanning and preservation of hides. Without this expertise, the trading enterprise likely would have failed. By the mid-nineteenth century, the reciprocity of indigenous women is demographically confirmed, in fifty-three distinct Métis communities in the Great Lakes area alone, whose inhabitations blended native and European ways of living in highly distinct ways.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.633
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.011
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0390.009

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 head0.024
GPT teacher head0.211
Teacher spread0.187 · 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 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
Published2017
Admission routes1
Has abstractyes

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