Information need, information seeking behaviour and participation, with special reference to needs related to citizenship: results of a national survey.
Bibliographic record
Abstract
This paper reports the results of the second stage of the Citizenship Information research project funded by the BLR&IC: a nation-wide survey, by personal doorstep \ninterview, of the citizenship information needs of almost 900 members of the UK public. \nMajor findings include: that the public obtain most of their information on current issues via the mass media, and that they generally feel well informed on these issues. The public feel, however, that government is not doing enough to inform them on European Monetary Union and on local government cutbacks. Small proportions of the sample had encountered problems concerning employment, education, housing or welfare benefits, and had consulted a range of information sources in order to overcome these problems. Over a quarter of respondents had experienced disadvantage through a lack of access to information. The \nmajority of respondents felt well informed about areas relating to citizenship, but significant proportions were poorly informed in legal rights, welfare benefits and local politics. A highly significant majority (91.7%) believed that freedom of information was important for exercising their rights as citizens. Respondents tended to overestimate their voting patterns, but there was little evidence of participation in other forms of political activity. Although access to computers in the home is presently limited, the majority of respondents would use computers to vote, convey opinions to government, and obtain government information. Public libraries were the preferred source of government information, and were seen as appropriate locations for a range of other types of citizenship information.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".