Living policy Labs: A case study of collaborative dialogue about social protection to alleviate grievances and facilitate peaceful outcomes in Egypt
Bibliographic record
Abstract
• An innovative ‘living policy lab’ inclusive of all stakeholders to develop equitable social protection policies is described. • Inclusive deliberation techniques are used to support co-creative behaviours aimed at enhancing community peace building . • Living policy labs are promising in contexts of structural violence where vulnerable groups might be socially excluded. Social protection may be regarded as the conduit for governments to end poverty (SDG1) and in turn maintain civil order/peace. However, how social protection is conceptualized alongside poverty ideology (who/what causes it and whose responsibility it is to relieve it) can negatively impact the development of social protection programs to the extent that they do not meet the social and economic needs of beneficiaries/end-users. Underpinning these views are social and political dynamics that reflect a wide range of sometimes opposing interests and social divisions. Thus, social protection inadvertently risks becoming a conduit to conflict rather than peace. In this paper we report on a living policy lab (LPL) we developed in Cairo (Egypt) to help mitigate this risk. The aim of the LPL was to facilitate dialogue between various stakeholders to support collaboration towards policy-making. First, we present an in-depth review of extant literature, discussing the viability of a ‘living policy lab’ approach to social policy making in MENA countries such as Egypt that are susceptible to conflict. Using Egypt as our focus, we critically outline its evolution of non-targeted to targeted programs and initiatives to alleviate poverty, arguing that they have been reactive and piecemeal rather than thought through (except for the universal health insurance system). We then examine findings from a project in Egypt involving a series of interrelated living policy labs (2018–2019) on social protection reform that involved a range of social actors. The aim was to explore whether, as a design process, the approach might offer an alternative shared power model that facilitates agreed policy priorities and in so doing mediates peace. In this way, we add to the scholarship on social protection by considering to what extent new approaches to policy making in contexts of conflict can support more sustainable and peace-promoting social protection interventions. We end the paper by providing recommendations in terms of research, policy and practice particularly in relation to future possibilities for consultative design theory.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".