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Record W3138474984 · doi:10.1007/s11759-021-09418-x

Archaeology, Participatory Democracy and Social Justice in Newfoundland and Labrador, Canada

2021· article· en· W3138474984 on OpenAlexaffabout
Lisa Rankin, Barry C. Gaulton

Bibliographic record

VenueArchaeologies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIndigenousGeneral partnershipDemocracyIndustrialisationParticipatory action researchEconomic JusticeUrbanizationPolitical scienceSociologyGeographyArchaeologyEconomic growthPoliticsAnthropologyLaw

Abstract

fetched live from OpenAlex

Abstract Memorial University, located in St. John’s, Newfoundland and Labrador, was created in 1925 to help build a better future for the people of Canada’s easternmost province, whose largely rural fishing communities were rapidly transforming through industrialization and urbanization. Mandated by a “special obligation to the people of the province,” university archaeologists embraced applied, community-based projects which encouraged local solutions to the social and economic issues arising from the transformation to modernity. Today, community archaeology remains integral to our research program and the majority of our research is undertaken in partnership with rural and Indigenous populations who continue to be marginalized both geographically and economically. Two case studies describe how archaeological resources are being used to promote economic and social justice, as well as reconciliation, and how archaeology has the potential to make valuable local contributions that change lives in the present.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0370.018
Scholarly communication0.0110.002
Open science0.0030.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.041
GPT teacher head0.299
Teacher spread0.257 · 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 designQualitative
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

Citations10
Published2021
Admission routes2
Has abstractyes

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