Moving Together Towards Collective Access (Dispatch)
Bibliographic record
Abstract
We Move Together (WMT) (Fritsch et al., 2021) is a picture book that follows a mixed-ability group of children as they move around their city community.We see the children move in different ways -fast, slow, using their feet as well as wheelchairs, scooters, crutches, bikes, and canes.Along the way, the kids encounter a great many people and animals, as well as a number of obstaclescommunication barriers, inaccessible infrastructure, political disagreements, etc. -that they work together to navigate.With regard to these obstacles, sometimes the work of moving together looks like building ramps, pivoting to a more inclusive game, or learning American Sign Language (ASL).Other times, this work looks like slowing down, sitting with disagreement, or taking a break.It is in part through navigating these challenges that the children encounter, relish in, and in turn grow disability community and culture.The children's commitment to moving together -their desire for collective as opposed to individual forms of access -deliver them into new political and artistic spaces, justice-oriented cultural formations that center disabled life, celebrate disabled joy, and encourage the flourishing of the widest array of bodies, minds, and movements.In Figure 1 the children can be seen at the center of such a flourishing: an abundance of disabled life and politics.It is as much a celebration of how our individual bodies and minds are and move, as it is a fulcrum of social movements moving together in solidarity, dreaming of, and fighting for better futures for all of us.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".