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Record W4412884820 · doi:10.1111/aman.28104

“Like We're Meeting the Ancestors”: Toward an Lˈnucentric Archaeology in Miˈkmaˈki

2025· article· en· W4412884820 on OpenAlexaff
Michelle A. Lelièvre, Cynthia L. Martin, Sarah Brooks, Hannah R Martin

Bibliographic record

VenueAmerican Anthropologist · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsCape Breton UniversityNova Scotia Department of AgricultureAssembly of First Nations
Fundersnot available
KeywordsArchaeologyHistoryAnthropologySociology

Abstract

fetched live from OpenAlex

ABSTRACT We explore the possibilities for an archaeology that is relevant to, and empowering of, Indigenous futures by reflecting on four seasons of archaeological fieldwork, our encounters with Lˈnu (or Miˈkmaw) material culture, our experiences returning to ancestral Lˈnu places, and our engagements with sociocultural and archaeological anthropologists and Indigenous studies scholars who have been debating the merits of community‐based collaborative research projects for the past three decades. Drawing on Linda Tuhiwai Smith's definition of decolonization, we suggest that a not‐quite‐here future Lˈnucentric archaeology in Miˈkmaˈki would not seek to imitate Western archaeological conventions, but change them. Our efforts to change archaeology have included expanding the scope of what counts as relevant archaeological data. We record both empirical observations related to artifacts, features, and stratigraphy, and also moments when our work has provided opportunities for our Lˈnu coauthors to meet their ancestors.

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)0.020
metaresearch head score (Gemma)0.011
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 score0.986
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0270.049
Scholarly communication0.0140.014
Open science0.0020.011
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.386
Teacher spread0.355 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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