Is technical demography becoming less relevant? Two decade review of published articles in selected demography journals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: In this paper, we reviewed development in the field of technical demography and empirically demonstrate that there has been a decline in the proportion of technical demographic studies published in the last two decades.Methods: All original articles published in nine demographic journals from Africa, Europe, Australia, Canada and United States were reviewed. We derived yearly aggregate for total number of articles and number of technical demographic papers from 1994 to 2015. We illustrated the trends in the proportion of technical demographic studies in a graph and also estimated the annual rate of decline using least square regression techniques.Results: A total of 4091 studies were published in 465 issues of the selected journals between 1994 and 2015 of which 371 (9.0%) were related to technical demography. The proportion of technical demographic papers declined gradually at an annual rate of 0.42% (CI= 0.29-0.62) between 1994 (12.0%) and 2015 (10.0%).Conclusion: Technical demography need to be strengthened in order to provide the critical data and evidence required to objectively monitor the post-2015 development goals.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it