Planning to maintain the status quo? A comparative study of digital equity plans of four large US cities
Bibliographic record
Abstract
The term digital equity is at the forefront of municipal government planning to mitigate digital equity. Digital equity signifies a desired future to be achieved, yet its meaning is not well-established. As such, planning for digital equity offers an opportunity for new discursive construction. This study examines how municipal governments have constructed the concept of digital equity through textual evidence, the digital equity plans of Kansas City, MO, Portland, OR, San Francisco, CA, and Seattle, WA. Adopting an approach from critical discourse studies, comparative analysis of the texts demonstrates how digital equity plans conceive of digital equity, characterize current problematic circumstances, and prescribe actions to make change. The plans have strikingly little to say about why digital inequality has emerged, yet they prescribe actions that indicate a more complex understanding of the problem than they articulate. The dynamics of policy diffusion suggest that the work of early adopters will influence other municipalities to create similar plans. Thus, the current moment is ripe for scholars to influence municipal planning for digital equity and participate in its discursive construction in both academic research and policymaking circles.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".