History and scientific background on the economics of abortion
Bibliographic record
Abstract
BACKGROUND: Approximately one quarter of all pregnancies globally end in abortion, making it one of the most common gynecological practices worldwide. Despite the high incidence of abortion around the globe, the synthesis of known economic outcomes of abortion care and policies is lacking. Using data from a systematic scoping review, we synthesized the literature on the economics of abortion at the microeconomic, mesoeconomic, and mesoeconomic levels and presented the results in a collection of studies. This article describes the history and scientific background for collection, presents the scoping review framework, and discusses the value of this knowledge base. METHODS AND FINDINGS: We conducted a scoping review using the PRISMA extension for Scoping Reviews. Studies reporting on qualitative and/or quantitative data from any world region were considered. For inclusion, studies must have examined one of the following outcomes: costs, impacts, benefits, and/or value of abortion-related care or policies. Our searches yielded 19,653 unique items, of which 365 items were included in our final inventory. Studies most often reported costs (n = 262), followed by impacts (n = 140), benefits (n = 58), and values (n = 40). Approximately one quarter (89/365) of studies contained information on the secondary outcome on stigma. Economic factors can lead to a delay in abortion care-seeking and can restrict health systems from adequately meeting the demand for abortion services. Provision of post-abortion care (PAC) services requires more resources then safe abortion services. Lack of insurance or public funding for abortion services can increase the cost of services and the overall economic impact on individuals both seeking and providing care. CONCLUSIONS: Consistent economic themes emerge from research on abortion, though evidence gaps remain that need to be addressed through more standardized methods and consideration to framing of abortion issues in economics terms. Given the highly charged political nature of abortion around the world, it is imperative that researchers continue to build the evidence base on economic outcomes of abortion services and regulations.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".