Rethinking heritagization through the digitization of familial archives
Bibliographic record
Abstract
This article interrogates the process of heritagization that occurs through the creation of the website dedicated to Léo Gravelle, a former Montreal Canadiens hockey player. This website, created by Léo Gravelle’s son, became an alternate venue to circulate and render accessible his professional hockey career by featuring private photographs alongside newspaper clippings, memorabilia and other personal archives. As a way to provide a wide exposure of Léo’s hockey past, facilitate public access to his personal archives that had been accumulated over many years, and ensure their preservation in the future, the creation of this website sheds light on heritage practices realized on a small and familial scale, at the intersection of unofficial heritage, digital heritage and familial heritage. Drawing on an analysis of the website and an interview conducted with the Gravelles, the article explores how this process of heritagization is framed – and transformed – by the possibilities provided by digital technologies, as well as by the cultural practices and familial ties that lie at the heart of the project The analysis of the digital heritagization practices initiated by family members occurring within the context of consumer culture and sport-spectacle opens up and challenges the way heritage is generally understood and established.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".