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Record W4310495315 · doi:10.51952/9781529222036.ch066

Access to Justice

2022· book-chapter· en· W4310495315 on OpenAlexaboutno aff
Rachel Hale

Bibliographic record

VenueBristol University Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Access to justice is a fundamental human right. Whilst there is no single definition, accessible justice typically refers to fair and widely understood laws, access to adequate legal supports and services, impartial and equitable justice system procedures and the right to recourse where these things are not experienced. A broader contemporary definition acknowledges ‘extra-legal’ factors, such as inequalities in health, housing and employment, which create and perpetaute barriers to justice. The notion of accessible justice posits that individuals interacting with the justice system should be treated fairly and equally, regardless of class, ethnicity, indigeneity, age, gender, sexuality and ability. Accessing justice therefore demands an inclusive system which enables active participation (see Canadian Forum on Civil Justice, 2015). The justice system, and associated services, should be accessible in terms of cost, language, distance and physical space, so as not to exclude or obstruct individuals from pursuing justice. It is important to acknowledge the significance of access to informal customary justice, particularly for Indigenous persons. Access to justice is central to the ‘rule of law’ – a core ideological principle of modern Western democracies – though this does not necessarily guarantee access. Contrastingly, in developing countries, particularly post-conflict authoritarian regimes, access to justice is relatively deficient and may not be an aspiration of the state. Global disparities in the prioritization of access to justice highlight the impact of place – a central consideration in rural criminology.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.953
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.078
GPT teacher head0.280
Teacher spread0.202 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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