Bibliographic record
Abstract
The urban landscape of the Halifax Peninsula has altered greatly over the 11-year period from 2009 to 2019. While surges in development affect the city in a plethora of ways, one of its most significant impacts is apparent in streetscape change This alteration of urban structure presents the opportunity to chronicle a city in transition. Utilising the theory of creative destruction to situate the findings, the primary aim of this study is to describe and capture the effects of a newly invigorated development climate long characterised by stagnation. Employing Google Street View as a source of visual data for comparative analysis, this study demonstrates the utility of public domain software in studying built landscapes. GIS provides additional veracity in quantifying morphological change. Findings reveal that peninsular Halifax has undergone rapid transformation as a result of redevelopment, resulting in intensified land usage and densification. Most prevalent amongst study sites are multi-storey mixed-use structures, in contrast to previously smaller scale land uses. New built forms display a high degree of homogeneity common to urban centres across North America; while these developments are largely concentrated within the downtown core, they increasingly encroach into surrounding neighbourhoods and threaten local heritage. Development activity will likely have various social and economic implications, representing uncertainties for existing and potential residents in the form of new uses of urban space.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.019 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| 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".