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Record W3215349324 · doi:10.1177/0308518x211060842

Land, land banks and land back: Accounting, social reproduction and Indigenous resurgence

2021· article· en· W3215349324 on OpenAlexaffabout
Matthew Scobie, Glen Finau, Jessica Hallenbeck

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNew Zealand Economic and Social Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCommodificationIndigenousAotearoaSocial reproductionReproductionCapitalismCountermovementSociologyEnvironmental ethicsGeographyPolitical scienceEconomySocial scienceEcologyEconomicsLawBiologyPoliticsGender studiesSocial capital

Abstract

fetched live from OpenAlex

This paper situates Indigenous social reproduction as a duality; as both a site of primitive accumulation and as a critical, resurgent, land-based practice. Drawing on three distinct cases from British Columbia, Canada, Aotearoa New Zealand and Bua, Fiji, we illustrate how accounting techniques can be a key mechanism with which Indigenous modes of life are brought to the market and are often foundational to the establishment of markets. We argue that accounting practices operate at the vanguard of primitive accumulation by extracting once invaluable outsides (e.g. Indigenous land and bodies) and rendering these either valuable or valueless for the social reproduction of settler society. The commodification of Indigenous social reproduction sustains the conditions that enable capitalism to flourish through primitive accumulation. However, we privilege Indigenous agency, resistance and resurgence in our analysis to illustrate that these techniques of commodification through accounting are not inevitable. They are resisted or wielded towards Indigenous alternatives at every point.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.036
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.196
Teacher spread0.175 · 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

Citations24
Published2021
Admission routes2
Has abstractyes

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