Bibliographic record
Abstract
I grew up in a family that left Communist Poland in the 1980s, and so it seemed a little unusual to me that I became interested in giving a voice to Polish Canadian Communists and their movement.Several factors motivated this decision.My family settled in Roncesvalles Village in the heart of Toronto's old Polish community along Roncesvalles Avenue, where most major Polish community organizations established their presence after World War II.The streets were lined with Polish deli shops, bakeries, and homestyle restaurants that offered everything from cabbage and potato-stuffed pierogi to regional kiełbasa and barszcz.Roncy is still a bustling neighbourhood, and although it has retained much of its Polish flare, the population has profoundly changed.When we lived there, the community was inhabited mainly by ex-soldiers, displaced persons, and former refugees who had refused to return to People's Poland after the war, and it was replenished in the 1980s by "solidarity wave" immigrants, such as my parents, who supported Lech Wałęsa and the anti-Communist movement in Poland.I grew up in a patriotic neighbourhood (and household).As a child, I was encouraged to read the Three Polish Bards, Adam Mickiewicz, Juliusz Słowacki, and Zygmunt Krasiński; I learned about important Polish leaders such as Józef Piłsudski and Tadeusz Kościuszko; and almost every year my family gathered at the Katyn memorial to commemorate the murder of over 20,000 Polish officers and intellectuals by the Soviets in 1940.Many Poles in the area organized patriotic folk dances, music festivals, and picnics, and most Polish parents sent their children to Polish-language school.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".