Bibliographic record
Abstract
Weaving Relationships tells the remarkable, little-known story of a movement that transcends barriers of geography, language, culture, and economic disparity. The story begins in the early 1980s, when 200,000 Maya men, women, and children crossed the Guatemalan border into Mexico, fleeing genocide by the Guatemalan army and seeking refuge. A decade later, many of the refugees returned to their homeland along with 140 Canadians, members of “Project Accompaniment”. The Canadians were there, by their side, to provide companionship and, more significantly, as an act of solidarity. Weaving Relationships describes the historical roots of this solidarity focusing on the Maya in Guatemala. It relates the story of “Project Accompaniment” and two of its founders in Canada, the Christian Task Force on Central America and the Maritimes-Guatemala “Breaking the Silence” Network. It reveals solidarity’s impact on the Canadians and Guatemalans whose lives have been changed by the experience of relationships across borders. It presents solidarity not as a work of charity apart from or “for” them but as a bond of mutuality, of friendship and common struggle with those who are marginalized, excluded, and impoverished in this world. This book speaks of a spirituality based on community and justice, and challenges the church to move beyond its preoccupation with its own survival to solidarity with those who are suffering. It is a book about hope in the face of death and despair.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.072 | 0.022 |
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".