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Record W7126533240

The possibilities of solidarities and resistances in the context of the claimant-lawyer collaboration on the preparation of an asylum claim

2023· article· en· W7126533240 on OpenAlexaboutno aff
Charlotte Dahin, Intersectional solidarities and resistances in face of violent migration regimes

Bibliographic record

VenueDigital Access to Libraries · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeContext (archaeology)ImmigrationPower (physics)Representation (politics)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

The Canadian refugee determination process (the context studied in my thesis) is a complex process that is difficult to navigate without assistance. As the process is particularly complicated, people claiming refugee status may be represented by a lawyer or other counsel, which happens in most cases (Rehaag, 2011). It has already been shown that representation is a critical element in the success of an asylum application (Rehaag, 2011). This paper is concerned with the claimant-lawyer relationship in this context and, more specifically, with the possible solidarities and resistances that can emerge from this relationship as part of preparing an asylum claim. Although the claimant-lawyer relationship is marked by a significant power differential, certain solidarities and resistances emerging in this context have already been highlighted in the literature. For example, the role of immigration representatives and refugee claimants and their way of working together in choosing what to write about in the asylum forms regarding prevailing Western norms and expectations have already been explored (Jacobs & Maryns, 2022; Oxford, 2008, 2016). Gender, race, class, and other intersecting axes of social division play a role in this context as they impact not only the client-lawyer relationship but also the expectations of decision-makers towards refugee claimants (Oxford, 2008). In this paper, I present the part of the data I collected for my thesis (through semi-structured interviews with refugee women and lawyers and observations of their encounters) on this issue.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
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 score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.028
GPT teacher head0.326
Teacher spread0.299 · 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 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
Published2023
Admission routes1
Has abstractyes

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Same venueDigital Access to LibrariesSame topicMigration, Refugees, and IntegrationFrench-language works237,207