Best Practices: A Young Professor's Reflections on Higher Education and Democracy for a World Beyond Our Borders
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
Dr. Khristina Haddad is an assistant professor who has finished her fourth year in the Department of Political Science at Moravian College. Her teaching philosophy and practice are highlighted in our "Best Practices" feature in this issue of the Journal of College and Character. See http://collegevalues.org/pdfs/Haddad.pdf Having completed her Abitur in Stuttgart, Germany, she fell in love with political theory and the liberal arts at Reed College in Portland, Oregon, and continued her political theory studies at McGill University in MontrÉal, Canada. Dr. Haddad has taught at the University of Latvia in Riga as an instructor for Civic Education Project. In 2003, she graduated from the Political Science doctoral program at the University of Michigan-Ann Arbor. Her research addresses the political importance of how we think about time.
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 | 0.001 | 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 | 0.001 | 0.000 |
| 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