CANADIAN HEROIN SUPPLY AND THE AUSTRALIAN ‘HEROIN SHORTAGE’
Bibliographic record
Abstract
We wish to comment on the recent article by Wood et al. [1], which questioned whether law enforcement contributed to the Australian heroin shortage in 2001. We agree with Wood et al. that reductions in international heroin supply may have played a larger role than we supposed in the Australian heroin shortage. We stress, however, that we acknowledged in our paper that changes in source countries probably did play a role (p. 466) [2]. We have never claimed, as some of our critics have assumed, that law enforcement activity was the sole, or even the major explanation of the Australian heroin shortage. None the less, for the following reasons we doubt that Australian heroin shortage can be wholly or largely explained by a reduction in heroin production in source countries. First, the timing of the onset of the Australian shortage can be specified to within a month. There was a simultaneous reduction in heroin availability reported by heroin users throughout the whole of Australia that began in late December and early January 2001. Time-series analysis of a wealth of monthly data reflecting the size of the heroin market pointed strongly to the occurrence of an external ‘shock’ to the heroin supply system on that date (e.g. [3–8]). This was clearest in the most direct indicators of heroin use, namely, fatal and non-fatal drug overdoses [9,10]. It was echoed in data on heroin price, purity and availability [11,12]. All analyses pointed to January 2001 as the time when there was a substantial change in the heroin market. This was consistent with the reports of heroin users, treatment providers, police [13,14] and the researchers who conducted research on the ground to investigate this unique event [15,16]. There was no comparable event in Vancouver that was reported at the time by key informants whom we contacted when undertaking our analyses of the reasons for Australian heroin shortage [14]. Secondly, the size of the decrease in fatal and non-fatal overdose in Australia was much larger (as well as more immediate) than the smaller (and more gradual) decline in overdoses observed in Vancouver. This reduction also occurred in the much larger heroin market of Sydney and Melbourne (the capital cities of States where it has been estimated there were possibly 70 000 regular heroin users in 2000 [17]) than the much smaller Vancouver market (where it might be estimated that there were 2000 such users, estimated from the number of overdose deaths) where fewer than half of the injectors surveyed reported daily heroin use. Thirdly, if the decline in overdose mortality in Vancouver data can be used to estimate the contribution that declining supply may have made in Australia, then it would explain about half the observed decline in Australian overdose deaths. This still leaves open the possibility that high-level law enforcement contributed to the Australian shortage. Fourthly, we did not argue that heroin seizures directly affected heroin supply in Australia. Rather, we argued that large seizures deterred large-scale centralized heroin importation syndicates from importing heroin in large quantities into Australia. This is supported by the fact that the amount of heroin seized in Australia was much larger than that in Vancouver in terms of both the absolute size (total kg) and in terms of probable market share [18]. Such large seizures might be expected to have a larger deterrent effect on heroin importers when supply in source countries was declining. Fifthly, the hypothesis that source country supply wholly explains the Australian shortage does not explain why there was a much larger reduction in heroin supply in Australia than in Vancouver, when Australian cities have a much larger heroin market, and are geographically much closer to source countries in the Golden Triangle than Vancouver. We agree with Wood et al. that we should avoid premature acceptance of the hypothesis that law enforcement activities played a major role in the Australian heroin shortage, given the paucity of data in the literature indicating that law enforcement activities have large effects on the size of heroin or other drug markets. We also believe that scepticism should be responsive to evidence when something unusual happened, as our data indicate that it clearly did in Australia in January 2001. It would be unwise to rule out on a priori grounds the possibility that the Australian heroin shortage may have been one of those rare occasions in which law enforcement activities contributed to reduced drug supply.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".