The Internet as a Space for Anonymous Alcoholics during the SARS-COV-2 (Covid-19) Pandemic
Bibliographic record
Abstract
INTRODUCTION: For over a year, Poland, alongside the entire world, has been facing the SARS-COV-2 (COVID-19 pandemic). This emergency has caused an immense social crisis, affecting especially the individual. The lack of social activity, including direct communication, along severe limitations on public and professional lives, have become a threat to mental health of people in almost all countries of the world. This state can be particularly difficult and dangerous to people with addiction. In the recovery process for alcoholics, a special role is often played by the Alcoholics Anonymous groups. OBJECTIVES: Due to the pandemic, meetings of AA groups (as well as other therapeutic groups) have been suspended until further notice. Due to this - due to necessity, not choice - such groups have moved to the online space. This raises a question if internet group meetings can make up for the lack of AA group meetings in physical space. METHODS: The research had an exploratory character. It was conducted between the start of June and the start of July 2020. 225 people participated. The research was conducted using quantitative methods, using a questionnaire designed specifically for this purpose. RESULTS: The research results indicate that the COVID-19 pandemic affected almost all of our respondents. The way the AA meetings work changed. Compared to live meetings, the frequency of meetings increased, the satisfaction from participation simultaneously decreased. Major flaws of online meetings are seen in the discomfort of respondents: some people stopped attending meetings after they moved to the internet. The positive sides of online meetings mainly had to do with the possibility of meeting and contacting new people living far and with organisational matters. The frequency of attending therapy with specialists/therapists decreased during the pandemic, while the frequency of contact with one’s sponsor increased. The overwhelming majority of respondents declared that they did not break abstinence during the pandemic. Those who did were usually people who had spent little time (usually a year, five years at most) in abstinence. The pandemic did not influence subjective appraisal of life quality. CONCLUSION: Our research showed that after the pandemic, our respondents would prefer to return to traditional, live AA meetings, organized as they used to be before COVID-19. Online meetings would only serve a useful, but ultimately complementary role.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".