Employment Dynamics in Regional Labour Markets: An Application of Gross Flows Analysis
Why this work is in the frame
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Bibliographic record
Abstract
This paper uses gross flows data for regions to show how the chance of leaving employment varies from place to place within New Zealand and how this risk of leaving employment influences subsequent search behaviour. We define labour market risk as the failure to sustain a continuous income stream through employment. Estimates of employment risk are made by applying a linear logit model to selected transition probabilities estimated from a quarter to quarter gross flows matrix constructed from New Zealand Household Labour Force Survey returns for the 14 year period 1986to 1999. We show how the risk of employment separations increase as the size of regional labour markers declines and their demand for labour weakens and how the diminished opportunities for employment in the peripheral regions encourages active rather than passive searching among those who leave employment. In regions with relatively high labour demand leaving employment is more likely to be followed by withdrawal from the labour force. By contrast, labour leaving employment in the weaker, provincial, labour markets is more likely to be followed by active searching (and hence unemployment). The way in which employment risk modifies search behaviour across the country affects the unemployed rate, raising it in weak markets and lowering overstating it in strong markers both temporally and geographically.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it