Reconsidering the approach for Invasive Species Management in Ontario: a more focused framework as a solution to Institutional Fragmentation
Bibliographic record
Abstract
This thesis is an investigation of the disjointed movement of government and non-government organizations that has led to institutional fragmentation in invasive species management (ISM). This study explored management avenues at a localized level to better understand both the successes and barriers in implementation. The goal of this research was to provide a comprehensive perspective on ISM practices and challenges. Expert interviews focused on the structural components comprising the process and substance aspects of ISM. The study found that involvement in ISM across Ontario varies greatly. A network approach was used to form an alternative framework that: 1) identifies capacity and mandates of each involved stakeholder and 2) identifies how action is executed at each level. As a result, this research provides a possible solution to institutional fragmentation through the creation of a more focused framework that outlines stakeholders, scope, responsibilities, and roles for the management of invasive species.
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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.036 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".