Metropolitan Police Public Attitudes Surveys, 2000-2017/18
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p><span style="font-weight: bold;">January 2019: These data have been temporarily withdrawn while the depositor conducts a review of governance around data sharing and publication.</span><br></p><p>The <i>Public Attitude Survey</i> (PAS) is a well-established survey that was first conducted in 1983 to give the Metropolitan Police Service (MPS) an understanding of the views of residents across London. From April 2014 the Mayor’s Office for Policing and Crime (MOPAC) took responsibility for the survey, which measures Londoners' confidence in the police and provides information that helps to set the strategic direction for policing and support continuous improvement at borough level.<br> <br> The PAS is a continuous survey, based on a random sample of respondents at pre-selected addresses with a total of 3,200 Londoners normally interviewed face-to-face each quarter to yield an annual sample of 12,800 interviews. The survey is designed to achieve 100 interviews each quarter in the 32 London Boroughs (excluding the City of London) in order to provide a borough-level sample of 400 interviews in any 12-month rolling period. Users should note that data are not currently available for April 2004-December 2005, but commence again in 2006. <br> <br> For further information, see documentation and the <a href="https://www.london.gov.uk/what-we-do/mayors-office-policing-and-crime-mopac/data-and-statistics" title="MOPAC data and statistics">MOPAC data and statistics</a> webpages.<br> <br> Another MPS survey series, the <i>Metropolitan Police User Satisfaction Survey</i>, is held at the UK Data Archive under SN 7084.<br> <br> <b>Latest Edition Information</b><br> For the seventh edition (June 2018), data and documentation for Quarters 49-52 were added, extending the study coverage to 2017-18.<br> <br> </p>
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.013 |
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 it