Bibliographic record
Abstract
Community Household Panel survey between 1994 and 2001.With the assistance of the ESRI, respondents from three birth cohorts within the national sample were invited to opt in to the LHSC study.Interviews were conducted in 2007 and 2008.In the years following data collection, the life story interviews were archived at the Irish Qualitative Data Archive at Maynooth University, Maynooth, Co. Kildare, Ireland (www.iqda.ie) and made available to bona fide researchers through application to the IQDA.The complete LHSC project database comprises 113 life story interviews, life history calendars, and simple retrospective social network schedules.The archival collection comprises 100 life story interviews -the remainder of the material was judged by the research team unsuitable for archiving (most often because the material was too sensitive) or was withheld from archiving by the interviewee.In 2015/2016 the IQDA will make available the collection of 100 interviews, plus a collection of audio files from these interviews through the Digital Repository of Ireland (www.dri.ie) as part of a demonstrator project entitled Irish Lifetimes, funded through the Irish Government Programme for Research in Third Level Institutions, Wave 5. Ruth Geraghty is leading the project to develop Irish Lifetimes at Maynooth University.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.836 | 0.766 |
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".