Choice of emergency shelter: valuing key attributes of emergency shelters
Bibliographic record
Abstract
Purpose The purpose of this study is to examine people’s preferences for some of the key attributes of emergency shelters, including type, privacy level, location, spatial arrangement and pet-friendliness. Design/methodology/approach Choice experiment (CE) method was used in this study. A standard CE questionnaire was designed and completed by a sample of 293 residents of the Greater Toronto Area, Ontario (Canada), during the winter of 2015. Findings When using publicly provided shelters, people prefer to stay in hotels, places of worship and then community shelters, in that order. These findings correspond to the values that they place for various attributes through the CE survey. Findings show that responders place the highest values for emergency shelters that provide more privacy, located close to their home, and are pet friendly. Type of shelter and the “arrangement” attributes were not found to be as important and valuable. Research limitations/implications This study uses a convenient sampling method as such may not fully represent the study population. Practical implications Emergency shelter provision by local, regional and national governments cost significant amount of money and thus it is important that the society get the maximum benefit from it. This will be possible when users’ preferences are considered in planning, design, and operation of emergency shelters. The findings enable emergency managers to perform cost-benefit analysis an increase the efficiency of emergency shelters. Originality/value While previous studies have examined emergency-shelter types, characteristics and user-satisfaction levels, this is a novel study because it uses a choice experiment method to extract monetary values for key emergency-shelter attributes.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".