Bibliographic record
Abstract
A two step or two phase BALTA mapping process was identified in Vancouver in January 2007. The various timetable components of the proposed mapping and survey work April 2007 to March 2008 are laid out below. Phase 1 (April to September) Includes a wide range of work including: Short survey design for SE organizations and another short survey tool for intermediate organizations; Meeting of core team to develop draft questionnaire. Development of an information package for potential interviewees that explains the BALTA Project and our reasons for mapping the sector; Creation of a ‘Researcher Handbook” for future student researchers working on mapping; An online survey software review and a decision on same (this may involve some computing support from Athabasca University if we use PHP Surveyor, or on our own with Survey Monkey- Note AU has confirmed that they support PHP Surveyor and that we may use it); Web design for the online survey tool (including help features etc.); A field test of the online survey and software. Note: also we plan to share BALTA survey design with other nodes in order to ask for and incorporate feedback before we go live. Outputs (see timeline) - short survey design for review; ethics review; introduction package and researcher’s handbook; online survey software chosen and template design; field test; concurrent development of SE Master List to identify potential participants in BALTA survey (see below). Recruitment of a senior student and two summer graduate students (the former as Lena’s near and far future replacement. Phase 2 (September to March 2008) Continue and complete Short survey to all sectors; Ongoing long survey development; long survey handbook development; long survey online survey design; student training; Data entry and data archiving of first short survey; analysis and report writing about of short survey; web display of map findings, including revised Master lists of organization; analysis of categories.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.126 | 0.078 |
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".