Replication package: measurement coverage and comparative conditions for international student mobility in five Central Asian higher education systems
Year: 2026
Type: dataset
Abstract: Replication package for the article Where the indicators stop: measurement coverage and comparative conditions for international student mobility in five Central Asian higher education systems (Akhrorova & Ibragimov). The archive contains everything needed to reproduce every number, table and figure in the article. Nothing is typed in by hand. coverage_audit.csv — the coverage audit behind Table 1: one row per candidate indicator, one column per system, recording whether the publishing organisation actually reports a value, plus the retention decision, the reason and the source URL consulted (24 rows: 23 candidate indicators plus the derived recognition indicator). treaty_sources.csv — per-country citations for every treaty membership in the typology: depositary record or national instrument, deposit date, date of entry into force for that party, source URL and confidence rating, covering the Lisbon Recognition Convention (ETS 165), the Asia-Pacific (Tokyo) Convention, the 2019 UNESCO Global Convention and EHEA membership. compute.py — holds the indicator values, derives the pairwise regional recognition coverage indicator from an unordered set of co-membership pairs, normalises and aggregates, runs the ceteris paribus gap-rule test reported in Figure 2A, runs the twenty-specification sensitivity suite reported in Figure 2B, and reports each indicator's regional range against its own scale. figures.py — regenerates Figures 1 and 2 at 400 dpi. routeA.json — machine-readable output: normalised values, condition scores, summary positions, the gap-rule comparison and every specification tested. revision_audit.txt — a machine-run check of the manuscript against each referee objection and each format limit. Figure1.tif, Figure2.tif — publication-resolution figures. README.md — what each file is and how to run the code. Reproducing: pip install numpy scipy matplotlib, then python compute.py and python figures.py. The computation is deterministic. Licensing: code under MIT, data and documentation under CC BY 4.0. See LICENSE.
Author: AKHROROVA, NILUFAR
Institution: Bukhara State University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7204266569