Bibliographic record
Abstract
For the past 30 years, young people have been growing up, existing, and producing data online. Their digital traces are distributed sporadically across the live and dead web, in corporately owned digital spaces, institutional holdings, and web archives. How these traces are theorized, studied, aggregated, deployed, or destroyed deserves increased public and academic attention. In this dissertation I argue that data is inextricably attached to people, both in the ways that it represents them and in the ways that they desire and deserve meaningful control over it. To this end, I propose an ethico-methodological intervention called an “archive promenade,” and developed Care Ethics Scaffolding for research with archived youth data that engages with feminist ethics of care to bring people back in relation with their data when researching the historical web. How an individual’s digital traces came to be, and the ways in which they are connected or distanced from their data, is explored throughout Chapters 3-5 where I demonstrate findings from my qualitative research project, called Early Internet Memories. In this project, I asked millennial participants (b. 1981-1996) who grew up in Canada to describe their memories of growing up online and the digital spaces that they once used to occupy. I also demonstrate how relationships between young people and the internet are not inevitable but rather constructed through government and commercial interests in promoting and creating an ideal child subject to support the growth and development of a new industry. These relationships were also multiple and varied, reflecting intersections of race, gender, class, age, and geographic location, which worked to differentiate many young people’s experiences and memories of the web. I argue that by exploring these histories of growing up online, we can see the processes by which people become databound: attached to the data they have produced throughout their lives in ways that they both can and cannot control through their ability to socially modulate and determine their information privacy. This framing assists in theorizing the long-term implications of online engagement, digital privacy, and the effects of datafication on life and livability on the web.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".