Bibliographic record
Abstract
This is an accepted article with a DOI pre-assigned that is not yet published.This paper develops an empirically responsible account of the attention economy. Almost all existing philosophical accounts of the moral and psychological harms of the attention economy rely on vague metaphors and folk psychological theorizing about the nature of attention and control. Drawing on recent work from across the cognitive sciences, we argue that a valuationist approach provides a more empirically robust and conceptually rich account than prevailing models of the attention economy, which emphasize addiction, compulsion, and loss of control. The valuationist framework posits that decision-making, including attention allocation and self-control, is fundamentally driven by representations of value. We contend that the attention economy's impact is best understood as shaping these value representations that influence decision-making. Contrary to folk psychological notions of intractable urges or hijacked autonomy, we argue that users maintain the capacity for choice and control. Moreover, our account can still capture the common phenomenology of feeling 'pulled' towards digital distractions. The first half of the paper unpacks the valuationist framework, with a special emphasis on valuationist accounts of attention and control. The second half of the paper applies this framework to better understand the moral and psychological harms associated with the attention economy.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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; both teacher heads agree on what is shown here.
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".