The role of policy in supporting SSS – the case of Quebec
Bibliographic record
Abstract
Since the early 2000s, short sea shipping (SSS) is often associated with significant social and environmental benefits. To encourage a modal shift, several nations around the world have developed public SSS policies. However, the policies’ effectiveness are increasingly being questioned in the public arena. Therefore, the current article’s primary objective is to assess one of these SSS public initiatives’ legitimacy. In particular, we analyzed Quebec’s PREGTI initiative, which is designed to both reduce greenhouse gas (GHG) emissions and promote local SSS development. Our findings are based on a triangulated analysis of official PREGTI documents and semi-structured interviews with local marine-sector specialists (N = 36). The data analyses inspired the development of an integrative framework that includes four components that could explain the lack of SSS program credibility and interest. Our framework identified critical issues for consideration in SSS program development, including: 1) the institutional framework’s relevance; 2) its implementation challenges; 3) the program’s predictability; and 4) the credibility of government authorities. Ultimately, the present article provides a better understanding of the significant discrepancies between public SSS programs development and the needs of local maritime sector stakeholders.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".