Providing and confining mobility: the e-cargo bike as a technology of parenting
Bibliographic record
Abstract
The private car is widely used by parents as a technology to cocoon their children from car-dominated environments while facilitating structured opportunities for their development. Outside the car, parents travelling by active or public modes must intensively regulate their child’s mobilities. These parent-child mobilities can help to develop a child’s independent mobility in the future, without the car. In this study, I explore the unique experiences and practices of parent-child mobility with the e-cargo bike in the low-cycling context of Ireland. This analysis uncovers how e-cargo cycle parenting reproduces practices fundamental to car-parenting: providing mobility for children and confining mobility of children. As a (temporary) technology for providing mobility, the e-cargo bike was experienced as a superior form of automobility than the car for meeting everyday parental mobility demands. By segregating children from the street and immobilising them in a vehicle, the e-cargo bike functioned as a space of confinement. Unlike the car, the e-cargo bike afforded a unique sensitivity to the natural world and local environment. This enabled parents to train their children in local geography and responsible mobility, thereby building their competences for independent mobility in the future while normalising everyday mobility without the car.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".