Legitimacy and space in the use of technologies for environmental and social governance: The cases of human trafficking and COVID-19 contact tracing
Bibliographic record
Abstract
This article develops the concept of legitimacy to analyze the capacity of technologies such as phone apps to mobilize collective commitments to shared environmental and social outcomes by constituting new governance spaces. This concept of governance spaces highlights the variable configurations of technologies and their interactions with humans, and helps avoid the tendency to see technologies as passive relays that transmit power originating elsewhere, or, in contrast, to overstate the almost magical autonomous capacities of technology. The concept of legitimacy is valuable for evaluating the degree to which technologies are effective and deserving of support. The article draws on Mark Suchman’s distinction between pragmatic, moral and cognitive legitimacy, which correspond in turn to interests, ethical values, and facts. In contrast to more conventional state-centered conceptions of legitimacy, these aspects of legitimacy can be applied to governance spaces constituted by technologies. The article then examines and compares the cases of technologies for countering human trafficking and COVID-19 digital contact tracing apps. In both cases all three aspects of legitimacy are present, important, and interconnected. An examination of a recent report issued by the Organization for Security and Cooperation in Europe and the Tech Against Trafficking coalition on 305 anti-trafficking tools shows the role of ethics and facts in their legitimacy, but also the degree to which the tools are skewed towards interests other than those at risk of being trafficked. Acceptance and evaluations of digital contract tracing apps are similarly shaped by the interactions between interests, ethical values, and facts, including evidence about their effectiveness. The legitimacy of COVID-19 digital contact tracing apps involves a wider presence of a public interest in health while the risks associated with power inequalities are greater with anti-trafficking technologies, highlighting the importance of variability in the legitimacy of governance spaces constituted by technologies.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.022 | 0.076 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".