- They cover actions with a view to anticipating the market and technological developments, investing in people on a permanent basis, developing employability, seeking alternatives to closures and redundancies, redeploying, whenever possible, workers affected by restructuring operations and so on - precisely those good practices which I hope will help Arcelor’s workers overcome the present difficulties, and which are dramatically absent in the Metaleurop environment.
- Den omfattar åtgärder i syfte att föregripa marknaden och den tekniska utvecklingen, investering i fast personal, utveckling av anställbarheten, sökandet efter alternativ till nedläggning och friställning, nyanställning, i möjligaste mån, av arbetstagare som drabbats av omstruktureringsåtgärder och så vidare - exakt sådan bra praxis som jag hoppas kommer att hjälpa Arcelors arbetstagare att komma över de nuvarande svårigheterna och som är så påtagligt frånvarande i Metaleurop.
- More importantly, the Commission very much hopes that the European social partners identify and find the means of developing good practices of corporate restructuring throughout the EU, as they decided to do when responding positively to last year’s consultation on this issue.
- Ännu viktigare är det att kommissionen verkligen hoppas att arbetsmarknadens parter i Europa kan hitta och använda de medel som behövs för att utarbeta en bra praxis för omstrukturering av företag i EU, vilket de gjorde när de reagerade positivt på förra årets samråd i den här frågan.
show query
SET search_path TO f9miniensv;
WITH
list AS (SELECT
t11.token_id AS t11,
t12.token_id AS t12,
t21.token_id AS t21,
t22.token_id AS t22,
r1.dep_id AS dep1,
r2.dep_id AS dep2
FROM
deprel r1
JOIN depstr s1 ON s1.dep_id = r1.dep_id
JOIN word_align a1 ON a1.wsource = r1.head AND a1.wsource < a1.wtarget
JOIN word_align a2 ON a2.wsource = r1.dependent
JOIN deprel r2 ON r2.head = a1.wtarget AND r2.dependent = a2.wtarget
JOIN depstr s2 ON s2.dep_id = r2.dep_id
JOIN token t11 ON t11.token_id = r1.head
JOIN token t21 ON t21.token_id = r2.head
JOIN token t12 ON t12.token_id = r1.dependent
JOIN token t22 ON t22.token_id = r2.dependent
WHERE
s1.val = 'amod' AND
s2.val = 'AT' AND
t11.ctag = 'NOUN' AND
t21.ctag = 'NOUN' AND
t12.ctag = 'ADJ' AND
t22.ctag = 'ADJ' AND
t11.lemma_id = 58122 AND
t12.lemma_id = 12586 AND
t21.lemma_id = 6899 AND
t22.lemma_id = 9885),
stats AS (SELECT
sentence_id,
count(DISTINCT token_id) AS c,
count(*) AS c_aligned,
count(DISTINCT wtarget) AS c_target
FROM
token
LEFT JOIN word_align ON wsource = token_id
WHERE
sentence_id IN (
SELECT sentence_id
FROM
list
JOIN token ON token_id IN(t11, t21)
)
GROUP BY sentence_id),
numbered AS (SELECT row_number() OVER () AS i, *
FROM
list),
sentences AS (SELECT *, .2 * (1 / (1 + exp(max(c) OVER (PARTITION BY i) - min(c) OVER (PARTITION BY i)))) +
.8 * (1 / log(avg(c) OVER (PARTITION BY i))) AS w
FROM
(
SELECT i, 1 AS n, sentence_id, ARRAY[t11,t12] AS tokens
FROM
numbered
JOIN token ON token_id = t11
UNION SELECT i, 2 AS n, sentence_id, ARRAY[t21,t22] AS tokens
FROM
numbered
JOIN token ON token_id = t21
) x
JOIN stats USING (sentence_id)
ORDER BY i, n)
SELECT
i,
n,
w,
c,
c_aligned,
c_target,
sentence_id,
string_agg(CASE WHEN lpad THEN ' ' ELSE '' END || '<span class="token' ||
CASE WHEN ARRAY[token_id] <@ tokens THEN ' hl' ELSE '' END || '">' || val || '</span>',
'' ORDER BY token_id ASC) AS s
FROM
sentences
JOIN token USING (sentence_id)
JOIN typestr USING (type_id)
GROUP BY i, n, w, c, c_aligned, c_target, sentence_id
ORDER BY w DESC, i, n;
;