Special Issue Review: "Dilemmas and Hopes for Human Rights Education: Curriculum and Learning in International Contexts", Edited by Felisa Tibbitts and Susan Roberta Katz
Bibliographic record
Abstract
Francisco, the collection explores some specific possibilities and challenges of Human Rights Education (HRE) in various contemporary settings, particularly from the standpoint of governmental education policy.A multitude of locations on different continents are included: Western Europe, China, Pakistan, India, Chile, and the United States.The underlying thread that connects these articles has to do with the search for truly * Ion Vlad, a native of Romania, is a recent graduate of the doctoral program in International and Multicultural Education, with a concentration in Human Rights Education, at the University of San Francisco.His dissertation explores the extent to which national human rights museums and centers in the United States and Canada engage in critical pedagogy and provide a 'third space' of dialogic education.Other research interests include the impact of globalization on human rights in post-Communist Eastern Europe, the role of emotion in peacebuilding and reconciliation after violent conflict, and the impact of the nation-state on the language of public-school textbooks.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".