Bibliographic record
Abstract
Distributed by Good DocsProduced by Andrea Schmidt and Shannon WalshDirected by Shannon Walsh2019, Streaming, 87 mins Illusions of Control chronicles the individual efforts of five women from vastly different cultures and backgrounds as they navigate their own trials and tribulations. At face value, director Shannon Walsh’s film appears to be about five cases of resilience. However, as the film progresses it becomes one narrative on resilience that transcends culture and geography. Walsh’s constant scaffolding of similar issues with dramatically different geographies is noteworthy as it unifies what are physically isolated communities. Some aspect of each case can be tied to another – dealing with potential exposure to environmental risks in Japan and Canada, concerns for the well-being of future generations in Mexico and China, and seeking closure on death in Mexico and the United States. Despite the uniqueness of each problem, the unifying element is the support systems aiding each individual. While the pacing initially feels off as the film jumps rather suddenly amongst the five main interviewees, the film does an excellent job of using other voices to provide cultural or social context to the issue at hand or how the issue is being handled. I would highly recommend the film for mental health counseling and social work students as both would benefit from exploring and discussing culturally sensitive approaches to resilience. Awards:Best Canadian Documentary, Honorable Mention, Calgary International Film Festival
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.006 |
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".