System Intertwining and Immigration Action Plans: The Case of a Provincial Funding Program in Quebec (Canada)
Bibliographic record
Abstract
The ability of political power to be deployed on several levels of governance is a key element of public administration, insofar as it enables the various needs of the population to be met. However, conflicts of competence, jurisdiction or vision can arise when it comes to articulating these different levels of management or intervention, particularly when policies with a broader scope are applied to local situations, thus proving ill suited to the realities experienced on the ground. This essay, with an example in the province of Quebec, illustrates how the provincial and municipal levels of governance—each with differing visions and objectives—are confronted with dilemmas respecting the constraints imposed by their levels of government. Through a systemic point of view, I show how intertwining systemic levels can produce conflicts since each has its own logic. This is explained with the example of a text-based mediated organization conducted by the “Programme d’appui aux collectivités” (PAC). The essay also identifies some challenges faced by civil servants working at two different levels of government as well as the place of the idea of resilience, and proposes recommendations.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".