Neoliberalism and government responses to Covid-19: Ramifications for early childhood education and care
Bibliographic record
Abstract
The Covid-19 pandemic has created an opportunity to examine the initial policies developed by Australian, Canadian, English, German, Greek and Irish governments to limit the spread of the virus. This has revealed governments’ conceptualisation of the early childhood sector and its workforce. This paper argues that neoliberal ideology and neoliberal imaginaries have already influenced the early childhood sector globally. During the pandemic, the choices that governments made at the outset of the pandemic has allowed their priorities and underlying ideology to be more transparent. Using an ethnographic methodology, early childhood researchers from each of the six countries, examined their individual governments policy responses and the effects on the early childhood sector during its initial months (between March and June 2020). The authors consider the extent to which this may have implications for the sector in how it should continue its ongoing pursuit of professionalisation of the sector. © 2022, Western Australian Institute for Educational Research Inc.. All rights reserved.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".