The Bank Manager Always Rings Twice: Stereotyping in Equity After Garcia
Bibliographic record
Abstract
Stereotyping is an inevitable part of human interaction. Everyone is judged, to some extent, according to individual perception, with reference to such factors as physical appearance, social position, marital status, language facility and ethnicity. It is not possible to eradicate stereotyping because it is a natural, automatic - sometimes instinctive - human response. In a legal context, however, there is a need for some mechanisms to control the degree to which stereotyping influences judicial decision-making so as to ensure that justice is administered in as neutral and impartial a manner as possible. Whether it be in the determination of facts by a trial judge or the development and expansion of legal principles within the appellate courts, legal decision-makers need to avoid using stereotypes in a discriminatory or prejudicial fashion. This may not always be easy because stereotyping can be an unconscious, indirect process - a judge may not even be aware that his or her assessment is prejudicial or impartial. Nevertheless, reducing the circumstances that are favourable to the perpetuation of discriminatory stereotyping is vital in an advanced system of justice. The more complex issue, however, is when to allow non-discriminatory stereotypes to be employed as an aid to decision-making. The aim of this article is to outline the variety of forms in which stereo- typing can manifest itself and distinguish discriminatory stereotyping against legally relevant stereotyping, especially in the context of equitable principle. To this end, we examine, in some detail, the High Court decision in Garcia v National Australia Bank Limited.2 We present this decision as a situation where the majority confirmation of an old equitable doctrine aimed at the pro- tection of a specific group of individuals provides a useful examination of the functional operation of stereotyping within the equitable jurisdiction. It is an approach that complements the fundamental methodology of equity. We illus- trate some of how this process operates by examining different examples of stereotyping used throughout the Garcia case as it made its way through the court system. The decision is then compared with the case of Louth v DiproseI where the creation of an equitable doctrine incorporating a large degree of subjectivity acts as a stimulus for discriminatory stereotyping.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".