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Record W2788576041 · doi:10.22329/wyaj.v34i2.5023

ANTICIPATING AND MANAGING THE PSYCHOLOGICAL COST OF CIVIL LITIGATION

2018· article· en· W2788576041 on OpenAlex
Michaela Keet, Heather Heavin, Shawna Sparrow

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCivil litigationPsychologySet (abstract data type)Value (mathematics)Economic JusticePublic relationsState (computer science)Social psychologyBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Despite growing national attention on the costs of accessing justice, surprisingly little information has been collected about the psychological ‘costs’ of engaging in litigation. This article summarizes the health and psychology literature, to present a picture of the impact that litigation can have on litigants’ health, state of mind, life goals and social relationships. Set against professional obligations embedded in the lawyer’s role, we assert that awareness of the negative impacts of legal processes on the emotional and psychological functioning of clients is important. With greater awareness, lawyers can better assess the value of litigation, prepare their clients (and themselves) for litigation stress, and, where appropriate, take preventative actions to minimize the negative aspects of the litigation experience. With that in mind, we identify positive solution-oriented responses to preventing, reducing and alleviating litigation stress. These strategies focus on client-centred communication, supports and planning.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.174
GPT teacher head0.515
Teacher spread0.340 · 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