Bibliographic record
Abstract
ii The purpose of this research was to develop a deeper understanding of the formation, operation, and impacts of a networked learning community within a geographically and culturally diverse school district in British Columbia, Canada. The general approach used for this research was case study methodology. As such, the work must be appreciated as a whole and as a narrative of how something came to be the way it is; in other words, to arrive at a comprehensive understanding of the group under study: Who are its members? What are their stable and recurring modes of activity and interaction? How are they related to one another and how is the group related to the rest of the world? The primary data sources for the study were network participant interviews and documents related to the network. The main findings of the study include a deeper understanding of the impact Ministry and School District level policies and practice had on the network’s inception and evolution; the operational details and structure that supported the network in order to create the conditions for learning; and how the perceived success was based upon focused “teacher talk”. Implications for practice include an understanding of how seemingly simple system actions are influenced by a broad array of macro and micro socio-political actions, as well as the historical context of an organization. The research also suggests that networks are not an end in themselves or fit into a prescribed typology but constitute a shifting terrain with impacts beyond the life of the network. iii
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.358 | 0.165 |
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".