Sensemaking and the political–administrative interface: the challenges of strategically steering and managing a local public service
Bibliographic record
Abstract
Our study focuses on the relationship between elected officials and managers in the context of local services management. We analyse the political–administrative interface using Weick’s theory of sensemaking. Our research, based on the case of water services management in Montreal, shows that the loss of expertise in the public sector, coupled with a lack of political vision, leads to a mismatch between the actions envisaged by the managers and the resources available. The organizational purpose needs to be politically defined in order to achieve a reciprocal influence in policy making. This collaboration, or complementarity of politics and administration, allows shared sensemaking that is essential both to a management diagnosis in line with the organizational mission and to strategic decision-making which takes into account the civil servants’ recommendations. Points for practitioners Some urban infrastructures, such as water infrastructure, are neither easily visible nor accessible. Thus, there is sometimes a wide gap between managers’ interpretation of the situation and that of the citizens and elected officials. This is a challenge for the development of common sensemaking. Elected officials must be able to count on a competent civil service that provides them with reliable information, enabling them to make trade-offs with all the relevant facts at hand. It is also in the public interest that elected officials maintain strategic control of the water activity in order for public action to efficiently contribute to the political vision.
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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 | 0.030 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.063 |
| Scholarly communication | 0.026 | 0.017 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".