a Canadian, a Communist, and a Christian
Bibliographic record
Abstract
It has been seventy-five years since the end of the Second World War, an event that has since become one of the defining elements in European history. It has been commemorated across the continent by many different communities in many different ways. But the one thing that most communities seem to have in common is a preference to remember the war through the stories of people. However, the people we commemorate are not set in stone. The individuals that we remember have changed many times over. This thesis sets out to explore this part of war remembrance; the place of the individual in remembrance culture. I have traced the remembrance of Léo Major, Hannie Schaft and Johannes Post and the places they hold in their communities. By doing a close reading of the narratives surrounding these individuals I have identified three different communities; local, political, and religious who have each remembered their heroes in a similar way. The narratives are built in the same way, emplotted as a romance and aiming to identify its protagonists as unique objects in the historical field. Performed in a similar way, through street names, accolades and monuments. And rising at a similar time, largely when their communities felt marginalized or threatened. However, the moment these individuals rose to fame says a lot about the ways in which Dutch people identify with different communities; Johannes became famous first which signals a strong identification with religious community, then came Hannie who shows us that people identified with a political community and later a gender community and last was Léo who shows that in recent years people seem to have shifted towards local communities.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".