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Record W3011253140 · doi:10.1080/00958964.2019.1687412

Place, Land, and the Decolonization of the Settler Soul

2019· article· en· W3011253140 on OpenAlexaff
David A. Greenwood

Bibliographic record

VenueThe Journal of Environmental Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsLakehead University
Fundersnot available
KeywordsDecolonizationSoulWonderHomecomingSociologyPoliticsNegotiationAestheticsEpistemologyEnvironmental ethicsLawSocial sciencePolitical scienceHistoryPhilosophy

Abstract

fetched live from OpenAlex

My aim in this essay is to wonder where in the world I am now as a scholar of place and a lover of places, and to give some shape to where I have been. I begin by reflecting on how I came to discover that “place” matters—at a historical moment (the 1990s) in which academic interest in place surged. Next, I address some of the controversies and silences that surround critical pedagogies of place. Much of this discussion is inspired by diverse perspectives toward the difficult and contested work of “decolonization,” one of the primary aims of critical place study. Finally, I delve into my own uncertainties and hopes around decolonization: what I discuss here as the lifelong, generational project of cosmological homecoming—the cultivation of the soul. I hope to show that the politics of decolonization must be spacious enough for white settlers like myself to examine and cultivate our own interior worlds. Whatever its prospects, decolonization depends on human beings who know who and where they are, who and where they come from, and how to negotiate the interplay between the soul and the polis.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.047
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.003
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 head0.002
GPT teacher head0.218
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations36
Published2019
Admission routes1
Has abstractyes

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