Bibliographic record
Abstract
My paper was the first of four in a symposium entitled, “Full house: Global studies on parenting”. Other presenters in the symposium reported on parenting situations in Russia, East Asia, and Israel. While there was minimal feedback on my presentation, it was positive overall, although one person stated he preferred the PARQ measure of Parenting Style by Rohner over the Buri measure I used. I chose the Buri measure over other scales (including the PARQ) because it was designed specifically to assess parenting styles as originally described by Baumrind, it was used by dozens of researchers, and it had good reliability and validity. After the presentations we discussed the differences among the different cultures. For example, divorce still carries a high stigma in Hong Kong, so the overall number of divorces is low and children who live in stepfamilies (even more rare) currently have more behavioural problems than children from married families. However, we wondered whether the situation in Hong Kong is merely catching up to the one in the U.S. and Canada, in which divorce used to carry a strong stigma, but has been becoming more common. Negative effects of divorce and stepparenting have lessened as more people have experienced them. My next step will be to look into publishing my work, perhaps in one of the IARR journals: “Journal of Personal Relationships” or “Journal of Social and Personal Relationships”. One of the most striking aspects of the conference was the friendliness of the attendees. Some of them were regulars and had been meeting one another at IARR for years, but many were graduate students or new scholars. Regardless of how experienced they were, participants seemed very interested in meeting new people and were extremely friendly and helpful. For example, I was impressed by the woman who bought me a “sabra” from the market so I could taste this quintessential Israeli fruit, by the woman who offered me her hat and plastic shoes for surviving the Dead Sea, the woman who pointed out to me a symposium she thought I would be interested in, and the man who immediately opened his computer at lunch to find out whether any sunrise concerts were being performed when I would be at Masada. One thing I learned from the IARR conference is how popular the concept of Adult Attachment is. This may be partly because a past president of the association (Phil Shaver) was instrumental in creating the first questionnaire assessing adult attachment (Hazan & Shaver, 1987). The measure has undergone many revisions and is now called the Experiences in Close Relationships Revised scale (ECR-R), which was used by many participants at the conference. The concept is based on the original infant-caregiving attachment patterns observed by Bowlby and Ainsworth, but now tends to refer to the bond between intimate partners. An amazing amount of work has been conducted in this area that has consistently found that adults who have a secure attachment are more healthy than other adults in a number of areas. For example, people who demonstrate an avoidant attachment have been found to be more prejudiced, to have a greater tendency to deny the severity of cancer with which they have been diagnosed, and to be the first to run away from a room that was on fire (I wonder how they obtained ethics approval on that one!). Although I don’t think I’ll be able to apply adult attachment to my research in the near future, I was intrigued by some of the methods used. Apparently it is possible to prime a particular type of attachment regardless of an individual’s inherent attachment style by having him/her describe a particular type of relationship he/she has experienced. Another set of researchers reviewed online parenting discussion boards to analyze the types of issues that new parents face by studying their responses in a natural environment. To my surprise, the themes that arose were extremely similar to the issues that face-to-face interviews revealed to me during my doctoral dissertation almost 20 years ago. These were things that mothers told me no one talked about. It looks like they still don’t talk about them, as the people who posted found them to be unexpected. Will the use of online discussion boards change this phenomenon in the future? Only time will tell. Perhaps I will be able to find out at the next conference, in Chicago in 2012.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".