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Record W6891334637 · doi:10.3886/icpsr34616.v2

Social Weather Stations Survey [Philippines]: Quarter III, 2003

2013· dataset· en· W6891334637 on OpenAlexaboutno aff

Bibliographic record

VenueICPSR Data Holdings · 2013
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Government (linguistics)General Social SurveySurvey data collectionPublic usePanel survey

Abstract

fetched live from OpenAlex

Social Weather Stations Surveys are SWS-initiated national surveys of the general Filipino public. Dating from 1986, initially semi-annual, and quarterly since 1992, these surveys are meant to supplement, not duplicate, existing government statistics. They include both core indicators monitored regularly and items on contemporary issues. A standard Social Weather Survey has two questionnaires, one for the household head and one for a random adult. The Third Quarter 2003 Social Weather Survey was fielded August 30 to September 14, 2003, throughout the country. It used face-to-face interviews of 1,200 respondents divided into random samples of 300 each in Metro Manila, Balance Luzon, Visayas, and Mindanao. Adults, aged 18 years and older, were asked their views on issues concerning the general topics of economics, governance, politics, diplomacy, and society, as well as issues of current public interest in the Philippines. The survey also gathers information from household heads about the members of the household and household characteristics. Demographic variables include sex, age, religion, education, marital status, household composition, language use, and occupation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.203
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.010
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.015

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.

Opus teacher head0.115
GPT teacher head0.349
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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