VARIATIONS IN SENSE OF PLACE ACROSS IMMIGRANT STATUS AND GENDER: RELATIONSHIP TO AIR QUALITY PERCEPTIONS AMONGST WOMEN IN HAMILTON, ONTARIO, CANADA
Bibliographic record
Abstract
In the first paper, sense of place (SoP) is used to evaluate immigrant experiences in three small to medium-sized Canadian cites: Hamilton, ON; Saskatoon, SK; and, Charlottetown, PEI. First, quantitative analysis is used to compare SoP amongst immigrant and Canadian-born respondents in the three cities. Ordered logistic regression determined four significant predictors of SoP: income; age; neighbourhood length of residence and, city of residence. Despite an observed difference in evaluations of SoP between immigrants and Canadian-born individuals, regression analysis did not identify immigrant status as a significant predictor of SoP. The second paper employs a mixed-methods strategy to examine individual perceptions of air quality and sense of place amongst Canadian-born and immigrant women in Northeast Hamilton. Furthermore, the study aims to determine the influence of sense of place on local environmental perceptions. Qualitative focus group discussions suggest that Canadian-born women may be more aware, knowledgeable and concerned about large-scale air quality issues; however, the tension between economic and environmental needs hinders their sense of control. Quantitative survey results suggest that Canadian-born residents have a higher absolute value of sense of place than immigrants. Bringing together the qualitative and quantitative data suggests that sense of place may inform environmental perceptions.
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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 | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".