Heritage and Community in the Humber River Basin Region
Bibliographic record
Abstract
My ongoing research has focused on the Humber River Basin Region of Newfoundland, initially as part of the Humber River Basin project at Grenfell Campus, Memorial University, and now as an individual research project. Over the course of five years, I have been developing an environmental history of this region, including community histories and how these community histories relate to broader historical issues which have affected western Newfoundland in the past. In the course of this research, I have carried out a number of community case studies, in particular, the resettled community of Woods Island, the non-extant community of Crow Gulch, and others. I have engaged fellow scholars and researchers, university students, and community representatives in uncovering this collective history. Its main objective has been to make this regional history relevant as public history, develop an interactive website, disseminate this research in various scholarly venues, collaborate with specialists in other disciplines who are interested in similar issues of heritage and community sustainability, and welcoming its use by others including artists and writers. Based on my research and findings, my talk will focus on how one can develop an integrated understanding of a region's past, develop community history for purposes of both scholarly research and heritage tourism, and demonstrate why such studies enhance a sense of regional and community worth and identity. I would like to see my presentation shared by Roxanne Abbott, Woods Island Resettlement House and Historic Center in Benoit’s Cove, and Vice Chair of the Humber Arm South Historic Sites and Heritage Committee. She would describe how our collaborative effort has been taken up within the Town of Humber Arm South.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".