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Record W4386049651 · doi:10.3390/rel14091078

Decolonising Islam: Indigenous Peoples, Muslim Communities, and the Canadian Context

2023· article· en· W4386049651 on OpenAlexaboutno aff
Shadaab Rahemtulla

Bibliographic record

VenueReligions · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsIslamIndigenousColonialismContext (archaeology)EmpireIslamic studiesSolidarityDecolonizationPraxisSociologyReligious studiesPolitical scienceGender studiesLawTheologyHistoryPhilosophyPolitics

Abstract

fetched live from OpenAlex

The problem of empire has been a key theme in Islamic Liberation Theology (ILT). However insightful, ILT’s engagement with the category of empire has generally presumed a particular colonial configuration in which Muslims are located on the receiving “end” of power, being occupied by an external, non-Muslim force. But what about the presence of Islam within settler colonies, in which voluntary Muslim migrants are structurally complicit in the ongoing disenfranchisement of Indigenous peoples? Focusing on the Canadian context, I ask: How can we decolonise Islam in the settler colony? That is, how can Muslims address their own complicity with the settler colonial project, standing in solidarity with native peoples and revisiting their own faith tradition in the light of that praxis? I argue that decolonising Islam entails three hermeneutical moves: (I) gaining a critical understanding of the socio-historical context, namely, the history of empire on the land; (II) deconstructing the boundaries between “migrant” and “settler”, which actually serves to vindicate the former group, releasing them of accountability and responsibility; and (III) engaging in bold theological reflection on the Islamic tradition. This final theological step, I maintain, is a two-fold dynamic: expounding Islam as both a radical subject that decolonises and a problematic object requiring decolonisation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.290
Teacher spread0.260 · 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 teacher head, not a consensus.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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