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Record W2731186053

The litigant in person and the access to justice dilemma : quo vadis South Africa

2016· article· en· W2731186053 on OpenAlexaboutno aff
Estelle Hurter

Bibliographic record

VenueComparative and International Law Journal of Southern Africa · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsPhenomenonStatus quoDilemmaPolitical scienceLawAdversaryEconomic JusticeCommon lawNorm (philosophy)SociologyLaw and economicsComputer security
DOInot available

Abstract

fetched live from OpenAlex

In recent years much attention has been given to the ever-increasing phenomenon of litigants in person (also referred to as self-represented litigants or pro se litigants) in civil practice within common law countries, particularly in the United States of America, Canada, Britain and Australia. Although the common law has long accepted a litigant’s right in civil proceedings to litigate in person, legal representation has more or less been the norm for centuries. Despite a substantial body of research material that has been steadily building up around various aspects of self-represented litigants, many questions have still not been answered definitively, including the reason for the growth of this phenomenon. However, what is certain is that this phenomenon is placing all aspects of the various justice systems under tremendous pressure, including the adversary system itself. Although various common law countries have made huge strides in trying to understand the phenomenon, the various role players in South Africa’s judicial administration have paid little or no attention to litigants in person (despite a regular appearance of such litigants in our courts). As it is probably only a matter of time before our legal system comes under the same pressure experienced elsewhere, it is the purpose of this article to offer proposals to first, ameliorate and secondly, to manage the consequences of such expected pressure based on the experience of other common law countries.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.099
GPT teacher head0.354
Teacher spread0.256 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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