Bibliographic record
Abstract
Dusseldorp Skills Forum has commissioned this report to provide a comprehensive picture of the Learning Choices sector, to pull together the existing research and evidence, summarise the data and findings that are available, and identify the gaps in knowledge. A wide variety of ‘alternative’ (Learning Choices) educational programs have been developed in Australia aimed at (re-)engaging young people with education. Some of these grew out of interest in progressive and democratic approaches to education while others responded to policy pressures to enable more young people to complete school. However, alternative education in Australia is fragmented both as a sector of educational practice and as a field of research. This means we have only limited knowledge about the range of programs that exist. What we do know is that Learning Choices programs offer vital pathways to enable young people to remain in school or to return to complete their education. There is clear evidence for the need such Learning Choices programs address. Retention to Year 12 has stabilised at around 75% since the mid-1990s (ABS, 2010). The retention rate for Indigenous young people continues to lag well behind at only 45% (Purdie and Buckley, 2010). The OECD provides comparative data for what it calls upper secondary attainment. The secondary school drop out rate is given as 14.7% for Australia compared to 12.9% for the OECD and 11% for the European Union (OECD, 2009). More than 16% of 15-19 year olds in Australia are not fully engaged and nearly a quarter of 20 to 24 year-olds: that is not in full time education or full time work (FYA, 2010, p.5; p.22). The concern grows when considering those 15-24 year olds who completed Year 10 or below: almost 57% are not fully engaged in the year after leaving school (FYA, 2010, p.21). Early school leaving has been linked to increased likelihood of unemployment, underemployment, crime and ill-health (AIG and DSF, 2007; BCA, 2003; FYA, 2010). The policy response has been to negotiate a national agreement on youth attainment and transitions: the National Partnership on Youth Attainment and Transitions. As part of this, the Australian Federal, State and Territory governments agreed to a target to raise the Year 12 (or equivalent) attainment rate to 90% by 2015 (CoAG, 2009, p.7). Achieving this target will require many young people who traditionally have left formal education ‘early’, for whatever reason, to remain in or return to education. Learning Choices programs play an important role in enabling these young people to attain Year 12 or equivalent qualifications and thereby assist governments to meet their target. Knowledge about the contribution Learning Choices programs make to engaging young people with education and helping them attain credentials is imperative. For the past decade Dusseldorp Skills Forum has built connections among Learning Choices programs through its Learning Choices expos in 2004 and 2006 and its Learning Choices website: www.learningchoices.org.au. In 2011, Dusseldorp Skills Forum further developed this by conducting a national survey of Learning Choices programs and initiatives. The ‘Learning Choices National Scan’ used the definition of “those programs/schools that cater for young people at risk of not completing their education”. More than 400 individual entries were made by the end of the survey period. Although inevitably not all relevant programs are included, this is the most comprehensive database of Learning Choices programs currently available. This report draws on data from the National Scan, supplemented with reports from individual programs (see Appendix 1) and existing research publications (see Appendix 2 for a selected annotated bibliography) to provide an overview of alternative education provision in Australia.
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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.019 | 0.030 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".