Bibliographic record
Abstract
This course examines the differential impact of ideologies on institutionalizing injustice. Exploring the ideological and institutional elements of law is important and regrettably much of the mainstream literature on law ignores both dimensions. Typically, contemporary legal scholarship fails to locate institutions within the broader context of ideologies. Likewise, studies on ideologies rarely implicate the detailed operations of institutions. The incredible absence of the ideo-institutional dimensions of criminal law is a serious concern that needs to be addressed. Despite the proliferation of critical criminological research that has succeeded in bringing the institutional dimension over to the ideological, there is still a need for an ideologically-oriented analysis of the institutional role of law. Further, an analysis of the interaction between ideologies and institutions is promising in understanding how legal injustices are reproduced. The main burden of this argument will be that an adequate grasp of the two fields may best be attained by conceptualising them as interlocking spaces within a broader conceptual frame of injustice. This course asks a range of interrelated questions about the relationship between ideologies and institutions; that is, criminal law is not simply a contest where the scales of justice are tipped in favour of the powerful but rather that the very essence of law (ideologies and institutions) is injustice. The aim of this course is threefold: first, to provide the conceptual tools necessary to understand the law; second, to present classic and contemporary debates regarding law and justice; and third, to demonstrate the impact of ideologies on institutionalizing injustices in an effort to argue that law is injustice.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".