Accountability literacies and conflictual cooperation in community-based organisations for young people in Québec
Bibliographic record
Abstract
Introduction In recent years, there has been an increasing interest in the rise of neoliberal practices and their effects on third sector organisations such as community-based organisations (Bradford and Cullen, 2014; Darby, 2016), which include the professionalisation of the sector and the use of monitoring and accountability systems. Bradford and Cullen describe how youth work, as a field, went through major changes in England, especially from the 1960s and 1970s until today, describing a shift from humanist perspectives to a focus on neoliberal and ‘value for money’ approaches. Community-based organisations have to demonstrate their value for money and therefore compete with each other to obtain limited financial resources (Darby, 2016). They have to engage with a wide range of literacy practices (for example, form filling) to obtain funding, as well as in order to justify it (for example, accountability reports). These can be described as accountability literacies: ‘the reading and, particularly, writing practices associated with accountability systems’ (Tusting, 2012: 121). In this chapter, literacies are considered as social practices rather than technical skills (Barton and Hamilton, 2012). Since the beginning of the 1990s, the Québec government has increased its involvement with community-based organisations such as Le Bercail and L’Envol partly because of their potential economic benefits for society and the state. These organisations received more recognition but were also increasingly seen as the state's services providers (Savard and Proulx, 2012). As in other countries, this led to the rise of an accountability regime that focuses on standardisation and monitoring systems (Ade-Ojo and Duckworth, 2015). In the Québec context, Duval and her colleagues (2005: 23) describe the complex relationship between community-based organisations and the state as the paradoxical position of ‘conflictual cooperation’: the organisations receive funding from the state but also maintain a critical stance towards the state in order to defend and advocate for the people attending their activities. Conflictual cooperation therefore implies a complex amalgam of resistance and collaboration. The aim of this chapter is to understand how youth workers at Le Bercail and L’Envol managed to navigate this accountability regime and its literacies.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".