Social Weather Stations Survey: 2015 Second Quarter
Bibliographic record
Abstract
Household facilities (1); labor force status (1); job search (4); ability & willingness to start a job (2); occupation information (3); working hours (4); jobs abroad (4); relatives abroad (2); household composition (2); self-rated poverty (6); food poverty (4); hunger (2); transportation expenses (1); past spending participation (6); future spending participation (6); media access (6); internet use (2); economic trend indicators (2); optimism/pessimism (2); news events (14), P-Noy (1); after P-Noy (1); noting preferences in 2016 election (13); President Benigno Aquino lll (5); leadership (1); political families (1); awareness/ratings of government officials (18); Cynthia Villar (2); awareness/performance of government institutions (10); performance of the national administration (20); Bangsamoro basic law (6); peace process with the government and MILF (4); dealing with armed groups (2); views on Muslims (3); communist rebels (3); budget management (6); grassroots budgeting (3); Janet Lim Napoles Case (3); former President Gloria Macapagal-Arroyo (2); awareness and trust in selected personalities (11); awareness and trust in institutions (4); international relations (7); Police (5); crime victimization (15); Maguindanao Massacre (3); agree/disagree statements (10); morale indicators (3).
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.012 |
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".