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Record W7054839522

Autonomy and minority groups : Different notions of autonomy and First Nations people

2024· article· en· W7054839522 on OpenAlexaboutno aff

Bibliographic record

VenueDiVA at Umeå University (Umeå University) · 2024
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyIndividualismOrder (exchange)WishConstruct (python library)Liberalism
DOInot available

Abstract

fetched live from OpenAlex

As a result of colonialism, many First Nations minorities have to a large extent lost their autonomy. They wish to be self-determined, but as a consequence of oppression, First Nations people have a deeply rooted mistrust of the state. This has made it more complex for the society to support autonomy for these groups. In this thesis my aim is to investigate how society can support autonomy for First Nations people - which notion(s) of autonomy is/are more applicable. As autonomy often refers to the liberal notion of autonomy with individualistic implications, some argue that autonomy is not applicable to groups. Therefore, I also explore the possibility whether the relational notion of autonomy is more relevant for supporting First Nations people autonomy. Even though I find liberal notion helpful for many minority groups, the relational notion has more applicable criteria in order to support autonomy for most minority groups as they define themselves through relations more than having individualistic interests. This is shown to be especially true for First Nations people. I have found that what distinguishes First Nations people from other minority groups is their connection to their land which can be explained through their spiritual notion of sovereignty. This profound connection defines who they are and the way they live. Therefore, I conclude that the relational notion is not sufficient to support autonomy for First Nations People, their spiritual connection with their land should also be considered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.005
GPT teacher head0.146
Teacher spread0.141 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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