The Significance of Place in Textual and Graphical Representation: The Mi'kmaq on Lennox Island, Prince Edward Island, and the Penobscot on Indian Island, Maine
Bibliographic record
Abstract
This research examines representations of indigenous identity and islandness rooted in place. The significance of this qualitative study is to enlarge human discourse on the semiotic interpretations of symbols in indigenous island cultures. If geography helps to shape identity, then identity, in turn, helps to shape place. This is a field study of signs and symbols used by the Mi'kmaq and Penobscot to represent their identity. Nissology assists in determining sense of place and in examining constructed textual and graphical representations of islandness. Documented photographs are examined through a bi-focal lens that is socio-cultural and socio-political. Elements of cultural and historical descriptions are identified in street signs, tourism and corporate signs, photographed on or in close proximity, to Lennox Island, Prince Edward Island, and Indian Island, Maine. Significations of identities are based on these visual images "catalogued, studied, distilled, and sorted into themes" (Harper, 1994). Ethnographic content analysis of the images is used to deconstruct the importance of the elements contained within each photograph. This is followed by image-based analysis of the two data sets and then compared. Findings indicate a complexity of multiple and hybrid identities used in different contexts depending on the interpretant.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".