HMDHFDplus: Read Human Mortality Database and Human Fertility Database Data from the Web
Bibliographic record
Abstract
Utilities for reading data from the Human Mortality Database (<<a href="https://www.mortality.org" target="_top">https://www.mortality.org</a>>), Human Fertility Database (<<a href="https://www.humanfertility.org" target="_top">https://www.humanfertility.org</a>>), and similar databases from the web or locally into an R session as data.frame objects. These are the two most widely used sources of demographic data to study basic demographic change, trends, and develop new demographic methods. Other supported databases at this time include the Human Fertility Collection (<<a href="https://www.fertilitydata.org" target="_top">https://www.fertilitydata.org</a>>), The Japanese Mortality Database (<<a href="https://www.ipss.go.jp/p-toukei/JMD/index-en.html" target="_top">https://www.ipss.go.jp/p-toukei/JMD/index-en.html</a>>), and the Canadian Human Mortality Database (<<a href="http://www.bdlc.umontreal.ca/chmd/" target="_top">http://www.bdlc.umontreal.ca/chmd/</a>>). Arguments and data are standardized.
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 | 0.017 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".