Nazita Lajevardi’s: Outsiders at Home: The Politics of American Islamophobia
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.
Bibliographic record
Abstract
This paper aims to understand the structure of actors involved in the increase of the number of lawyers in Korea. For this research, the Canadian Scholar’s Policy Network Approach and the Sabatier’s Advocacy Coalition Concept were used. The case analysis focuses on the policy decisions related to the number of people passing the bar examination. This paper reviewed the policy debates, initiatives and actions of actors concerned before and during the 1995 legal reform process. The research result is as follows: The Supreme Court, the prosecution and the national bar association have been a very powerful and very organized policy community affecting the issues mentioned. As a sub-government, they have played a key role in deciding the number of lawyers in the country. They have effectively prevented the issues affecting their interests from being policy agenda. However, the law professors’ associations and civic groups remained as an attentive public. A policy network highly represented by the lawyers’ community, which appears to be clientele oriented, existed for a long time. However, during the reform, the structure of the policy network changed a lot. As the presidential office initiated the reform, the attentive public participated in the core policy making process. In relation to this, the network changed from clientele oriented to a cooperative one. In addition, there was policy learning between the groups. Policy makers must realize that it is necessary to collaborate with the attentive public and at the same time change the structure of the policy network. This is to modify the policy which has been unchanged because of the existence of the strong policy community. This paper also proves that the irregular policy making process, such as reform, could be more effective and that policy learning is very important for the policy change.
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 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 | 0.000 | 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 it