Markets, Privatisation and Justice: Some Critical Reflections
Bibliographic record
Abstract
Today, we do not know what we have to do, but we have to act now, because the consequences of inaction could be catastrophic. (Žižek 2011, 480) There's Something Different Going On – Have You Noticed? We are in the vice-like grip of an acute paradox. At the critical moment when neoliberal capitalism has entered its latest crisis, the relentless pursuit of profitable markets on the back of neoliberal dogma is infiltrating an expanded set of organisational domains. At the precise historical juncture when lessons could be assimilated to modify if not rid the world of a failed and failing political economy where money is the ultimate standard of value, desperate attempts are being made to resuscitate an ailing system by prescribing more of the same rather than deciding that enough is enough. However, the unfolding catastrophe which is being played out in the global market place of ideas and material conditions, manifested in an ecological crisis, struggles over raw materials, deepening and widening social divisions (Žižek 2011), has not gone without challenge, protest, or resistance. The Occupy Movement in Madrid during May 2011, with eruptions on Wall Street in September, subsequently established its presence in other cities and countries. In fact, one of us was directly affected by the movement when travelling from Ottawa to Toronto on Saturday, 15 October 2011 to return from Canada to the United Kingdom.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.057 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".