Beyond Window Rainbows: Collecting Children’s Culture in the COVID Crisis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As COVID-19 dramatically alters the museum sector, museums and archives are implementing collection initiatives that will have tremendous influence over how the pandemic is understood and remembered. As collections experts, museums are leading the charge to document, collect, and interpret our current circumstances as they unfold in real time, relying more than ever on public participation and crowd-sourcing. A key development in such rapid-response collecting has been the interest in and solicitation of contributions that document the current crisis. Yet, initiatives that target young people remain few and far between, and often reproduce romanticized and reified understandings of children and childhood that reflect a longer history of excluding children’s voices from museum collections and society at large. This paper will explore museums’ collection of children’s culture in various forms with attention to the epistemological and ethical challenges that such initiatives entail. We argue that children are crucial citizens whose knowledge, perspectives, and experiences must be collected and preserved during this historic moment and beyond, in ways that attend to the particular circumstances they face as multiply marginalized museum constituents and members of society.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it