Boldly Going Where No Law Has Gone before: Call Centres, Intake Scripts, Database Fields, and Discretionary Justice in Social Assistance
Bibliographic record
Abstract
This article focuses on the response of public law to bureaucratic disentitlement. Whether eligibility decisions for social welfare benefits are made on the basis of a face to face interview or telephone intake screening at a call centre, whether the questions are onerous for vulnerable applicants to answer, whether the bureaucratic hurdles can reasonably be surmounted or lead to the de facto exclusion of otherwise eligible applicants, all constitute questions which should be fundamentally intertwined with the question of whether a discretionary decision is legally valid. This is so not only because service delivery models and administrative design may determine the fairness, reasonableness, and accuracy of a decision, but also because forms of administration ought not to be inconsistent with our fundamental values, such as human dignity. This article advocates a more robust, public law response to the welfare system than courts have been willing to undertake, This approach requires that judges look beyond the veil of public administration and ensure that the rule of law reaches all spheres of public authority. Changing the welfare system, however, ultimately requires changing political and bureaucratic, as well as legal, culture.
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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 | 0.033 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.062 |
| Scholarly communication | 0.023 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".