Bibliographic record
Abstract
Rethinking Children and Clothes is a photo book designed to register the relationship children have with the garments in their wardrobes. I produced and photographed children in the intimate setting of their home, aiming to explore identity development during the transition from childhood into adolescence. Here, the clothes have emotional significance, durability that surpasses the physical integrity of the fabric. The photographs focus on the wear and tear, holes, stains, and rips that become part of much loved, worn clothing. The pictures show details of the dressed body, preserving the privacy of the subject but revealing aspects of their identity. Based on Sally Mann’s work with her family and discussions about children as research participants, this project is a conversation between fashion and childhood. I intend to propose a different way of seeing identity in a visual medium that is removed from identification. Additionally, the materiality of clothing, their “thing-power” (Bennett 348), demand their existence as objects of discourse between a child and society. The participants were invited to edit the final product and to share their thoughts in a brief interview. With this work, I suggest that wearing worn out clothing creates an emotional connection, preserving garments that do not have to be discarded or replaced so swiftly.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".