Insta-judgement: Irony, authenticity and life writing in mothers’ use of Instagram
Bibliographic record
Abstract
Abstract This article aims to explore the ways that photos and written texts using the hashtag #assholeparents extend understandings of both life writing theories and the field of motherhood studies. At first glance, this hashtag seems to stray from picture-perfect Pinterest parenting. A closer analysis, however, reveals that despite the seeming rejection of model parenting, the pictures and texts grouped by #assholeparents nonetheless affirm deeply normative views of parenting in general and of motherhood in particular. As such, while largely featuring children, these photographs can arguably stand as maternal self-portraits. This examination aims to explore a collection of images as examples of a composite form of life writing. The use of life writing as a critical practice allows for an analysis of the images and accompanying text that aims to pull the camera back and view the context and motivations outside the frame. The particular use of Instagram further complicates the notion of life writing by presenting each image as an independent text but also as part of an emergent composite memoir that borrows from and contributes to idealized notions of family.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".