MIrreM Public Database on Irregular Migration Stock Estimates
Bibliographic record
Abstract
The Public Database on Irregular Migration Stock Estimates (the Database) provides an inventory and critical appraisal of country-level estimates of irregular migration stocks in 13 European countries, the United States and Canada for the period 2008 to 2023. It is a deliverable of the MIrreM project, which is a follow-up to Clandestino. Clandestino covered the period 2000-2008. Users of the Database are advised to consult the following companion documents: The README File (version 2), which can be accessed alongside the Database, and contains contextual and technical information about the Database. Discussion of the context, the underlying concepts, and the methodology used in the data collection and quality assessment: Vargas-Silva, C., Leerkes A., Kierans, D., Siruno, L. and Kraler, A. (2024, forthcoming). Tools for collecting information on irregular migration estimates and indicators. Open Research Europe. Analysis of the stock estimates: Kierans, D. and Vargas-Silva, C. (2024). The Irregular Migrant Population of Europe. MIrreM Working Paper No. 11. Krems: University for Continuing Education Krems (Danube University Krems). https://doi.org/10.5281/zenodo.13857073 Furthermore, users of the Database are notified of a ‘sister’ database of the MIrreM project, which captures and assesses estimates and indicators of irregular migration flows over the same period, the Public Database on Irregular Migration Flow Estimates and Indicators and accompanying analysis: Siruno, L., Leerkes, A., Badre, A., Bircan, T., Brunovská, E., Cacciapaglia, M., Carvalho, J., Cassain, L., Cyrus, N., Desmond, A., Fihel, A., Finotelli, C., Ghio, D., Hendow, M., Heylin, R., Jauhiainen, J.S., Jovanovic, K., Kierans, D., Mohan, S.S., Nikolova, M., Oruc, N., Ramos, M.P.G., Rössl, L., Sağiroğlu, A.Z., Santos, S., Schütze, T., & Sohst, R.R. (2024) MIrreM Public Database on Irregular Migration Flow Estimates and Indicators. Krems: University for Continuing Education Krems (Danube University Krems). https://doi.org/10.5281/zenodo.10813413. Siruno, L., Leerkes, A., Hendow, M. & Brunovksá, E. (2024) Working Paper on Irregular Migration Flows. MIrreM Working Paper No. 9. Krems: University for Continuing Education Krems (Danube University Krems). https://zenodo.org/records/10702228
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.118 |
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; both teacher heads agree on what is shown here.
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".