CHGS Newsletter - January 2013 - Special Edition: International Holocaust Memorial Day
Bibliographic record
Abstract
January 2014 is a special edition for International Holocaust Memorial Day and includes: On Good and Bad Memory, Genocide and its Aftermaths: Lessons from Rwanda, Local Holocaust Survivor and Friend of CHGS Gustav "Gus" Gutman dies at 78, Holocaust Survivor Dora Zaidenwber's talk now available to view on CHGS YouTube Channel, Eye on Africa: Seeds of Genocide in the CAR: What we need to know, Interview with Flim Producer, Director Noemi Schory, CHGS Director Alejandro Baer to Lecture on Global Holocaust Memory and the New Antisemitism, War, Genocide, and Justice: Cambodian American Memory Work, Panel Discussion: Remembering the Holocaust in Literature, Film, and Theology, Course: Special Screening of Granito: How to Nail a Dictator with Filmmakers Pamela Yates and Paco Onís, and Book of the Month: Commemorating the Holocaust: The Dilemmas of Remembrance in France and Italy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.003 |
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; both teacher heads agree on what is shown here.
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".