Bibliographic record
Abstract
This is one of over 400 major media market consumer surveys which have been gifted to Washington State University (WSU) by Leigh Stowell & Company, Inc. of Seattle , Washington , USA . This is a market research firm which specializes in providing newspapers, television affiliates and cable operators with market segmentation research pertinent to consumer purchasing patterns and the effective marketing of goods and services to program audiences. The data in the Stowell Archive were collected via random digit dialing and computer-aided telephone interviews (CATI). Most of the surveys focus on the marketing needs of mass media clients and contain demographics, psychographics, media exposure information, and purchasing behavior data about consumers in major metropolitan areas of the United States and Canada starting in 1989. The sample sizes of the surveys range from 500 to 3,000 respondents, averaging 1,000 observations per study. Data are available at the respondent level, and all observations are keyed to zip code or other geographic identifiers. Additional surveys are anticipated, with over twenty new media marke t studies being donated annually. The University's relationship with Leigh Stowell & Company, Inc. was cultivated by Dr. Nicholas Lovrich, Director of WSU's Division of Governmental Studies and Services (DGSS) and by Dr. John Pierce, former Dean of the WSU College of Liberal Arts over the course of a decade. DGSS collaborated with WSU Libraries Digital Services to process the gifted data files into this digital archive which features powerful search and download capabilities. Further refinement of the archive in accordance with the Data Documentation Initiative is progressing with support from the Office of the Provost, the College of Liberal Arts and the WSU Libraries. It is important to note that the year indicated by the study's title is the year that the original survey was published, and is not necessarily the year in which the interviews were conducted. Refer to the metadata field "Dates of Collection" to di scern the interview dates of each specific survey. Refer also to date fields within the data file itself.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.298 | 0.331 |
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".