Local people's “sense of place” toward cultural heritage sites: correlation with demographic and socio-economic characteristics
Bibliographic record
Abstract
Purpose The paper aims at identifying the underlying factors that differentiate the local people's demographic and socio-economic characteristics, which influence their sense of place (SoP) toward different types of cultural heritage sites in different urban regions. Design/methodology/approach The paper draws on the sequential explanatory design, using quantitative and qualitative methods, respectively, to investigate the research themes in-depth. A total of 201, 207 and 228 questionnaires were collected on religious, non-religious/memorial and historic commercial buildings, respectively, at two different quarters in Historic Cairo, followed by 20 semi-structured interviews with a representative sample of local people in each quarter. Findings The authors found an apparent similarity in the significant characteristics that influence the local people's SoP levels toward the different historic buildings at the same quarter and a notable variation between both quarters. Also, many factors determine the local people's influential characteristics on their SoP toward the different cultural heritage sites (e.g. the sites’ distance from the person's residence/workplace, economic value, people's awareness about its history, type of activities and targeted gender, feeling of stability and regions' characteristics) Practical implications Identifying these underlying factors and priority local groups can assist policymakers in ensuring a sustainable management/conservation of the different cultural heritage sites. Originality/value The paper demonstrates the causality of a significant correlation between local people's characteristics and their SoP levels toward the different types of historic buildings, apart from their religious symbolism or historical value, using the sequential explanatory design.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".