Critical junctures, labour unions, and social dialogue in Tunisia and Lebanon: Implications for the social contract
Bibliographic record
Abstract
This paper examines the evolution of social dialogue institutions in Lebanon and Tunisia between 2010 and 2017. Both countries faced critical junctures, but their institutions pursued divergent courses. The national social dialogue institution was revamped in Tunisia to increase participation in policymaking, whereas it was reinstated in Lebanon without addressing its institutional flaws. By building on these developments, this paper makes two theoretical contributions. First, it argues that the nature of political interference in organized labour prior to the critical juncture influences its subsequent role. Labour neutralization in Lebanon was founded on sectarian politics that co-opted national leadership and bound rank-and-file to sectarian clientelism. Labour pacification in Tunisia harmed executives, whereas local unionists remained independent. After the critical juncture, Tunisian organized labour revitalized itself, aided by rank-and-file autonomy. It then made a strategic choice to reconsolidate the tripartite system with enhanced involvement of the traditional labour and capital organizations in policymaking. Lebanese organized labour was unchallenged by its rank-and-file. It maintained ties with political elites. Second, these paths illustrate the differences between social contracts. Participation in policy elaboration is among the deliverables exchanged between political elites and social actors in Tunisia but not in Lebanon.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".