Bibliographic record
Abstract
Abstract This chapter examines the contemporary manifestations of the pilgrimage tradition of Hajj and engages a deeper reflection on how Muslim pilgrims encounter and negotiate space(s)—both physical and virtual—in a globalized, hyperconnected era. The embodied experiences of Hajj pilgrims in Mecca, Saudi Arabia, are examined through the lens of artefacts produced and publicly shared with others on social-networking platforms. A visual-content analysis conducted on a sample of one hundred selfies taken at Hajj point to the work that these artefacts do in the context of the construction of affiliative identities among geographically dispersed communities of pilgrims. Our findings suggest that the selfies contribute to interrogating and complicating religious spaces. The heterotopic discursive fields opened by the sacred selfies may even constitute meaningful ritual spaces through a recentering around the devotee. Sacred selfies can thus be read as a tactic used to create opportunities for self-representation and community building.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".