Bibliographic record
Abstract
Book synopsis: In late April, tens of thousands of people gathered to protest at the Second People’s Summit of the Americas (the FTAA Summit). RESIST! is a collection of young peoples’ experiences from Quebec City. Surprising in their honesty, these accounts, including poems, photos and essays, look at what happened during the FTAA weekend. The contributors seek answers to explain the treatment of the protesters, marvel at the strength of character of those that they encountered, and celebrate many successes. The material gathered here reflects the variety of people who felt compelled to go to the protests and talks about how they chose to participate. \n \nThe contributors found themselves on either side of the fence and in jails, and they watched as friends were harassed or taken away by police. They talk about their participation in the Saturday march, sleeping on gymnasium floors and being fed and taken care of. Amongst the personal stories are responses from many different groups and essays that analyse the FTAA, the anti-globalization movement and organizations involved in acts of resistance. \n \nAn engaging look at the Second People’s Summit of the Americas, RESIST! presents a much different experience from that depicted in the news coverage. It encourages all of us to be forward looking and to be active within our own 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 | 0.002 | 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 | 0.009 | 0.005 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".