Bibliographic record
Abstract
Distributed by Good DocsProduced by Ellen ReimerDirected by Ritchie Hemphill and Ryan Haché2023, Streaming, 16 mins Odette Auger, Local Journalism Initiative Reporter, windspeaker.com, writes that “Tiny is a short film about a strong woman,” and this reviewer couldn’t agree more. This 16-minute, Claymation stop motion film by Ritchie Hemphill and Ryan Haché captures historical memories from Ritchie’s mother, Nakwaxda’xw Elder Colleen Hemphill’s childhood. This style of storytelling and use of stop motion is effective in that the film sets a neutral and loving tone from an elder and reminds this reviewer of her own grandmother who pass down stories of how events and cultural landscapes have changed throughout history. Nicknamed Tiny and Queenie as a youth, Elder Hemphill, who also serves as the film’s narrator, shares memorable stories of what it is like to grow up on a float house in northern Vancouver. She learns many lessons from her parents, one of which is to be one with the earth and nature. She emotionally describes what it means to be a member of a tight-knit community during climate changes. Although further readings are an absolute must to learn more about the vast history of the Nakwaxda’xw people, and the contributions of activist Colleen Hemphill, I believe young adults to the general public will find this film engaging and take note of the importance of community, connection to nature, and intergenerational storytelling. It is a tradition that must be passed along to children, grandchildren, and future generations. I highly recommend this film for the expansion of Global and Indigenous studies. Awards:Best Documentary Short, DOXA Documentary Film Festival; Elevate Award, DOXA Documentary Film Festival; Best Animated Short, American Indian Film Festival; Best Indigenous Short, Regina International Film Festival; Best Canadian Short, Shorts Not Pants Film Festival; Best Short Award, Portland Ecofilm Festival; Shawash Ilihi Award, McMinnville Short Film Festival; Best Animated Short, Red Nation International Film Festival; Best Animation Award, Three Fires International Film Festival; Best Cinematography Award, Three Fires International Film Festival; Outstanding Animated Film, Short Circuit Pacific Rim Film Festival; Lodestar Award, Dawson City International Short Film Festival; Audience Choice Award, Salt Spring Island 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.843 | 0.713 |
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".