A Framework of Foreseen and Unforeseen Harms in Transformative Service Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Transformative service systems (TSSs) are designed to uplift human well-being. Yet, paradoxically, by necessity and in design, TSSs can also generate unintended harms for system actors. Our conceptual paper builds on recent service literature, as well as that on unintended consequences from a range of fields, to advance an integrative framework of harms in TSSs. Through the enabling theory of the doctrine of double effect, our framework organizes harms in the transformative service context, identifying that unintended harms can be both foreseen and unforeseen. Additionally, we find that the mechanism underlying these harms is system emergence. Emergence arises from the relative complexity of the service system and the relative dynamism of the issue the TSS aims to address. Our framework demonstrates that greater service system complexity increases the likelihood of foreseen harms, while greater relative dynamism increases the likelihood of unforeseen harms arising. Furthermore, we show how these two factors combine to promulgate the emergence of harms. We find that in instances where harm arises, greater service system adaption is required to mitigate such harms. However, some TSS harms are an inevitable and unfortunate secondary outcome of doing good, and these harms necessitate acknowledgment and acceptance by service designers.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 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 it