The Social Accountability Report within the Chambers of Commerce: Theory, Procedure and Empirical Evidence
Bibliographic record
Abstract
In Italy, many companies and central and local public administration offices, including the Chambers of Commerce, are turning to new forms of accounting of their results. Amongst these, the social accountability report definitely represents an innovative tool; an innovation intended to guarantee compliance with the principles of accountability and social control, that are growing strong within the wider process of transparency and accessibility of management data, as well as the use of the resources, which involves the whole Public Administration. The social accountability report is presented as a non-accounting tool meant to spread a systemic and structured vision of the activities carried out and of the results obtained by the administration in reference to the period of the ending mandate. The aim of the work is to examine in depth the issue of social reporting in the Chambers of Commerce, referring in particular to the social accountability report, highlighting its potential and its criticalities through a theoretical, empirical and methodological analysis. By using the empirical analysis, we are going to show, first of all, the composition and the territorial distribution of social reporting in the Chambers of Commerce between 1999 and 2016. By offering, later on, a case study, such as the social accountability report of the Chamber of Commerce of Treviso, we will show how the experiences of the Chambers of commerce relating to social reporting are so heterogeneous that the several reports produced often show some significant peculiarities on a structural level. In the knowledge that such heterogeneity represents, however, a methodological enhancement, the work will later show a standard social accountability report for the Chambers of Commerce that is a result of the adaptation and reasoned integration of the contents of the social accountability reports produced by the Chambers of Commerce so far.
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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 | 0.133 | 0.316 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.024 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".